Incremental flux allocation for LIDAR detection

ABSTRACT

A LIDAR system is provided. The LIDAR system comprises at least one processor configured to: control at least one light source in a manner enabling light flux to vary over a scan of a field of view; control projection of at least a first light emission directed toward a first portion of the field of view to determine an absence of objects in the first portion of the field of view at a first distance; when an absence of objects is determined in the first portion of the field of view, control projection of at least a second light emission directed toward the first portion of the field of view; and control projection of at least a third light emission directed toward the first portion of the field of view to determine an existence of an object in the first portion of the field of view.

CROSS REFERENCES TO RELATED APPLICATIONS

This application is a continuation of PCT International Application No.PCT/IB2017/001320, filed Sep. 20, 2017, which claims the benefit ofpriority of U.S. Provisional Patent Application No. 62/396,858, filedSep. 20, 2016; U.S. Provisional Patent Application No. 62/396,863, filedSep. 20, 2016; U.S. Provisional Patent Application No. 62/396,864, filedSep. 20, 2016; U.S. Provisional Patent Application No. 62/397,379, filedSep. 21, 2016; U.S. Provisional Patent Application No. 62/405,928, filedOct. 9, 2016; U.S. Provisional Patent Application No. 62/412,294, filedOct. 25, 2016; U.S. Provisional Patent Application No. 62/414,740, filedOct 30, 2016; U.S. Provisional Patent Application No. 62/418,298, filedNov. 7, 2016; U.S. Provisional Patent Application No. 62/422,602, filedNov. 16, 2016; U.S. Provisional Patent Application No. 62/425,089, filedNov. 22, 2016; U.S. Provisional Patent Application No. 62/441,574, filedJan. 3, 2017; U.S. Provisional Patent Application No. 62/441,581, filedJan. 3, 2017; U.S. Provisional Patent Application No. 62/441,583, filedJan. 3, 2017; and U.S. Provisional Patent Application No. 62/521,450,filed Jun. 18, 2017. All of the foregoing applications are incorporatedherein by reference in their entirety. All of the foregoing applicationsare incorporated herein by reference in their entirety.

BACKGROUND

I. Technical Field

The present disclosure relates generally to surveying technology forscanning a surrounding environment, and, more specifically, to systemsand methods that use LIDAR technology to detect objects in thesurrounding environment.

II. Background Information

With the advent of driver assist systems and autonomous vehicles,automobiles need to be equipped with systems capable of reliably sensingand interpreting their surroundings, including identifying obstacles,hazards, objects, and other physical parameters that might impactnavigation of the vehicle. To this end, a number of differingtechnologies have been suggested including radar, LIDAR, camera-basedsystems, operating alone or in a redundant manner.

One consideration with driver assistance systems and autonomous vehiclesis an ability of the system to determine surroundings across differentconditions including, rain, fog, darkness, bright light, and snow. Alight detection and ranging system, (LIDAR a/k/a LADAR) is an example oftechnology that can work well in differing conditions, by measuringdistances to objects by illuminating objects with light and measuringthe reflected pulses with a sensor. A laser is one example of a lightsource that can be used in a LIDAR system. As with any sensing system,in order for a LIDAR-based sensing system to be fully adopted by theautomotive industry, the system should provide reliable data enablingdetection of far-away objects. Currently, however, the maximumillumination power of LIDAR systems is limited by the need to make theLIDAR systems eye-safe (i.e., so that they will not damage the human eyewhich can occur when a projected light emission is absorbed in the eye'scornea and lens, causing thermal damage to the retina.)

The systems and methods of the present disclosure are directed towardsimproving performance of LIDAR systems while complying with eye safetyregulation.

SUMMARY

Embodiments consistent with the present disclosure provide systems andmethods for using LIDAR technology to detect objects in the surroundingenvironment.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light flux to vary over a scan of a field of viewusing light from the at least one light source; control at least onelight deflector to deflect light from the at least one light source inorder to scan the field of view; use first detected reflectionsassociated with a scan of a first portion of the field of view todetermine an existence of a first object in the first portion at a firstdistance; determine an absence of objects in a second portion of thefield of view at the first distance; following the detection of thefirst reflections and the determination of the absence of objects in thesecond portion, alter a light source parameter such that more light isprojected toward the second portion of the field of view than isprojected toward the first portion of the field of view; and use seconddetected reflections in the second portion of the field of view todetermine an existence of a second object at a second distance greaterthan the first distance.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light flux to vary over a scan of a field of viewusing light from the at least one light source; control projection of atleast a first light emission directed toward a first portion of thefield of view to determine an absence of objects in the first portion ofthe field of view at a first distance; when an absence of objects isdetermined in the first portion of the field of view based on the atleast a first light emission, control projection of at least a secondlight emission directed toward the first portion of the field of view toenable detection of an object in the first portion of the field of viewat a second distance, greater than the first distance; and controlprojection of at least a third light emission directed toward the firstportion of the field of view to determine an existence of an object inthe first portion of the field of view at a third distance, greater thanthe second distance.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light flux to vary over a scan of a field of view, thefield of view including a first portion and a second portion; receive ona pixel-by-pixel basis, signals from at least one sensor, wherein thesignals are indicative of at least one of ambient light and light fromthe at least one light source reflected by an object in the field ofview combined with noise associated with the at least one sensor;estimate noise in at least some of the signals associated with the firstportion of the field of view; alter a sensor sensitivity for reflectionsassociated with the first portion of the field of view based on theestimation of noise in the first portion of the field of view; estimatenoise in at least some of the signals associated with the second portionof the field of view; and alter a sensor sensitivity for reflectionsassociated with the second portion of the field of view based on theestimation of noise in the second portion of the field of view, whereinthe altered sensor sensitivity for reflections associated with thesecond portion differs from the altered sensor sensitivity forreflections associated with the first portion.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light intensity to vary over a scan of a field of viewusing light from the at least one light source; control at least onelight deflector to deflect light from the at least one light source inorder to scan the field of view; obtain an identification of at leastone distinct region of interest in the field of view; and increase lightallocation to the at least one distinct region of interest relative toother regions, such that following a first scanning cycle, lightintensity in at least one subsequent second scanning cycle at locationsassociated with the at least one distinct region of interest is higherthan light intensity in the first scanning cycle at the locationsassociated with the at least one distinct region of interest.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light flux to vary over scans of a field of view usinglight from the at least one light source; control at least one lightdeflector to deflect light from the at least one light source in orderto scan the field of view; receive from at least one sensor, reflectionssignals indicative of light reflected from objects in the field of view;determine, based on the reflections signals of an initial lightemission, whether an object is located in an immediate area of the LIDARsystem and within a threshold distance from the at least one lightdeflector, wherein the threshold distance is associated with a safetydistance, and when no object is detected in the immediate area, controlthe at least one light source such that an additional light emission isprojected toward the immediate area, thereby enabling detection ofobjects beyond the immediate area; when an object is detected in theimmediate area, regulate at least one of the at least one light sourceand the at least one light deflector to prevent an accumulated energydensity of the light in the immediate area to exceed a maximumpermissible exposure.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control light emission of a lightsource; scan a field of view by repeatedly moving at least one lightdeflector located in an outbound path of the light source, whereinduring a single scanning cycle of the field of view, the at least onelight deflector is instantaneously located in a plurality of positions;while the at least one deflector is in a particular instantaneousposition, receive via the at least one deflector, reflections of asingle light beam spot along a return path to a sensor; receive from thesensor on a beam-spot-by-beam-spot basis, signals associated with animage of each light beam-spot, wherein the sensor includes a pluralityof detectors and wherein a size of each detector is smaller than theimage of each light beam-spot, such that on a beam-spot-by-beam-spotbasis, the image of each light beam-spot impinges on a plurality ofdetectors; and determine, from signals resulting from the impingement onthe plurality of detectors, at least two differing range measurementsassociated with the image of the single light beam-spot.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one deflector todeflect light from a plurality of light sources along a plurality ofoutbound paths, towards a plurality of regions forming a field of viewwhile the at least one deflector is in a particular instantaneousposition; control the at least one deflector such that while the atleast one deflector is in the particular instantaneous position, lightreflections from the field of view are received on at least one commonarea of the at least one deflector, wherein in the at least one commonarea, at least some of the light reflections of at least some of theplurality of light sources impinge on one another; and receive from eachof a plurality of detectors, at least one signal indicative of lightreflections from the at least one common area while the at least onedeflector is in the particular instantaneous position.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: access an optical budget stored inmemory, the optical budget being associated with at least one lightsource and defining an amount of light that is emittable in apredetermined time period by the at least one light source; receiveinformation indicative of a platform condition for the LIDAR system;based on the received information, dynamically apportion the opticalbudget to a field of view of the LIDAR system based on at least two of:scanning rates, scanning patterns, scanning angles, spatial lightdistribution, and temporal light distribution; and output signals forcontrolling the at least one light source in a manner enabling lightflux to vary over scanning of the field of view in accordance with thedynamically apportioned optical budget.

Consistent with a disclosed embodiment, a vibration suppression systemfor a LIDAR configured for use on a vehicle may include at least oneprocessor configured to: control at least one light source in a mannerenabling light flux of light from the at least one light source to varyover scans of a field of view; control positioning of at least one lightdeflector to deflect light from the at least one light source in orderto scan the field of view; obtain data indicative of vibrations of thevehicle; based on the obtained data, determine adjustments to thepositioning of the at least one light deflector for compensating for thevibrations of the vehicle; and implement the determined adjustments tothe positioning of the at least one light deflector to thereby suppresson the at least one light deflector, at least part of an influence ofthe vibrations of the vehicle on the scanning of the field of view.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light flux of light from at least one light source tovary over a scanning cycle of a field of view, wherein the lightprojected from the at least one light source is directed to at least onedeflector to scan the field of view; receive from at least one sensorreflections signals indicative of light reflected from objects in thefield of view; coordinate light flux and scanning in a manner to causeat least three sectors of the field of view to occur in a scanningcycle, a first sector having a first light flux and an associated firstdetection range, a second sector having a second light flux and anassociated second detection range, and a third sector having third lightflux and an associated a third detection range, and wherein the secondlight flux is greater than each of the first light flux and the thirdlight flux; and detect, based on input from the at least one sensor, anobject in the second sector located at a distance beyond the firstdetection range and the third detection range.

Consistent with a disclosed embodiment, a LIDAR system, may include atleast one processor configured to: control at least one light source ina manner enabling light flux of at least one light source to vary over aplurality of scans of a field of view, the field of view including anear-field portion and a far-field portion; control at least one lightdeflector to deflect light from the at least one light source in amanner scanning the field of view; implement a first scanning rate forfirst frames associated with scanning cycles that cover the near-fieldportion and a second scanning rate for second frames associated withscanning cycles that cover the far-field portion, wherein the firstscanning rate is greater than the second rate; and control the at leastone light source, after projecting light that enables detection ofobjects in a plurality of sequential first frames associated with thenear-field portion, to alter a light source parameter and therebyproject light in a manner enabling detection of objects in the secondframes associated with the far-field portion.

Consistent with a disclosed embodiment, a LIDAR system for use in avehicle may include at least one processor configured to: control atleast one light source in a manner enabling light flux of at least onelight source to vary over scans of a field of view; control at least onelight deflector to deflect light from the at least one light source inorder to scan the field of view; receive input indicative of a currentdriving environment of the vehicle; and based on the current drivingenvironment, coordinate the control of the at least one light sourcewith the control of the at least one light deflector to dynamicallyadjust an instantaneous detection distance by varying an amount of lightprojected and a spatial light distribution of light across the scan ofthe field of view.

Consistent with a disclosed embodiment, a LIDAR system for use in avehicle may include at least one processor configured to: control atleast one light source in a manner enabling light flux of light from atleast one light source to vary over a scanning cycle of a field of view;control at least one deflector to deflect light from the at least onelight source in order to scan the field of view; obtain input indicativeof an impending cross-lane turn of the vehicle; and in response to theinput indicative of the impending cross-lane turn, coordinate thecontrol of the at least one light source with the control of the atleast one light deflector to increase, relative to other portions of thefield of view, light flux on a side of the vehicle opposite a directionof the cross-lane turn and encompassing a far lane of traffic into whichthe vehicle is merging, and causing a detection range opposing thedirection of the cross-lane turn of the vehicle to temporarily exceed adetection range toward a direction of the cross-lane turn.

Consistent with a disclosed embodiment, a LIDAR system for use with aroadway vehicle traveling on a highway may include at least oneprocessor configured to: control at least one light source in a mannerenabling light flux of light from at least one light source to vary overa scanning cycle of a field of view; control at least one deflector todeflect light from the at least one light source in order to scan thefield of view, wherein the field of view is dividable into a centralregion generally corresponding to the highway on which the vehicle istraveling, a right peripheral region generally corresponding to an arearight of the highway, and a left peripheral region generallycorresponding to an area left of the highway; obtain input that thevehicle is in a mode corresponding to highway travel; and in response tothe input that the vehicle is in a mode corresponding to highway travel,coordinate the control of the at least one light source with the controlof the at least one light deflector such that during scanning of thefield of view that encompasses the central region, the right peripheralregion, and the left peripheral region, more light is directed to thecentral region than to the right peripheral region and to the leftperipheral region.

Consistent with a disclosed embodiment, a LIDAR system may include atleast one processor configured to: control at least one light source ina manner enabling light flux of light from at least one light source tovary over a scan of a field of view; control at least one deflector todeflect light from the at least one light source in order to scan thefield of view; receive from at least one sensor information indicativeof ambient light in the field of view, identify in the receivedinformation an indication of a first portion of the field of view withmore ambient light than in a second portion of the field of view; andalter a light source parameter such that when scanning the field ofview, light flux of light projected toward the first portion of thefield of view is greater than light flux of light projected toward thesecond portion of the field of view.

Consistent with a disclosed embodiment, a LIDAR system for use in avehicle may include at least one light source configured to projectlight toward a field of view for illuminating a plurality of objects inan environment of a vehicle; at least one processor configured to:control the at least one light source in a manner enabling light flux oflight from the at least one light source to vary over scans of aplurality of portions of the field of view, wherein during scanning ofthe field of view, heat is radiated from at least one system component;receive information indicating that a temperature associated with atleast one system component exceeds a threshold; and in response to thereceived information indicating the temperature exceeding the threshold,modify an illumination ratio between two portions of the field of viewsuch that during at least one subsequent scanning cycle less light isdelivered to the field of view than in a prior scanning cycle.

Consistent with a disclosed embodiment, a LIDAR system may include awindow for receiving light; a microelectromechanical (MEMS) mirror fordeflecting the light to provide a deflected light; a frame; actuators;and interconnect elements that are mechanically connected between theactuators and the MEMS mirror; wherein each actuator comprises a bodyand a piezoelectric element; and wherein the piezoelectric element isconfigured to bend the body and move the MEMS mirror when subjected toan electrical field; and wherein when the MEMS mirror is positioned atan idle position, the MEMS mirror is oriented in relation to the window.

Consistent with other disclosed embodiments, a method may include one ormore steps of any of the processor-executed steps above and/or includeany of the steps described herein.

Consistent with yet other disclosed embodiments, non-transitorycomputer-readable storage media may store program instructions, whichare executed by at least one processing device and perform any of themethods described herein.

The foregoing general description and the following detailed descriptionare exemplary and explanatory only and are not restrictive of theclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this disclosure, illustrate various disclosed embodiments. Inthe drawings:

FIG. 1A is a diagram illustrating an exemplary LIDAR system consistentwith disclosed embodiments.

FIG. 1B is an image showing an exemplary output of single scanning cycleof a LIDAR system mounted on a vehicle consistent with disclosedembodiments.

FIG. 1C is another image showing a representation of a point cloud modeldetermined from output of a LIDAR system consistent with disclosedembodiments.

FIGS. 2A-2D are diagrams illustrating different configurations ofprojecting units in accordance with some embodiments of the presentdisclosure.

FIGS. 3A-3D are diagrams illustrating different configurations ofscanning units in accordance with some embodiments of the presentdisclosure.

FIGS. 4A-4E are diagrams illustrating different configurations ofsensing units in accordance with some embodiments of the presentdisclosure.

FIG. 5A includes four example diagrams illustrating emission patterns ina single frame-time for a single portion of the field of view.

FIG. 5B includes three example diagrams illustrating emission scheme ina single frame-time for the whole field of view.

FIG. 5C is a diagram illustrating the actual light emission projectedtowards and reflections received during a single frame-time for thewhole field of view.

FIGS. 6A-6C are diagrams illustrating a first example implementationconsistent with some embodiments of the present disclosure.

FIG. 6D is a diagram illustrating a second example implementationconsistent with some embodiments of the present disclosure.

FIG. 7 is a flowchart illustrating an example method for detectingobjects using a LIDAR system consistent with some embodiments of thepresent disclosure.

FIG. 8A is a diagram illustrating an example of a two-dimensional sensorconsistent with some embodiments of the present disclosure.

FIG. 8B is a diagram illustrating an example of a one-dimensional sensorconsistent with some embodiments of the present disclosure.

FIG. 9A is a block diagram illustrating an example LIDAR device havingalignment of transmission and reflection consistent with someembodiments of the present disclosure.

FIG. 9B is another block diagram illustrating another example LIDARdevice having alignment of transmission and reflection consistent withsome embodiments of the present disclosure.

FIG. 10A is a diagram illustrating an example first field of view (FOV)and several examples of second FOVs consistent with some embodiments ofthe present disclosure.

FIG. 10B is a diagram illustrating an example scanning pattern of asecond FOV across a first FOV consistent with some embodiments of thepresent disclosure.

FIG. 10C is a diagram illustrating another example scanning pattern of asecond FOV across a first FOV consistent with some embodiments of thepresent disclosure.

FIG. 11 provides a diagrammatic illustration of a field of view and anassociated depth map scene representation associated with a LIDARsystem, according to presently disclosed embodiments.

FIG. 12 provides a diagrammatic illustration of a field of view and anassociated depth map scene representation generated using a LIDAR systemwith a dynamically variable light flux capability, according topresently disclosed embodiments.

FIG. 13 provides a flow chart representation of a method for dynamicallyvarying light flux over a scanned field of view of a LIDAR system,according to presently disclosed embodiments.

FIG. 14 provides a diagrammatic illustration of a field of view and anassociated depth map scene representation associated with a LIDARsystem, according to presently disclosed embodiments.

FIG. 15 provides a diagrammatic illustration of a field of view and anassociated depth map scene representation generated using a LIDAR systemwith a dynamically variable light flux capability, according topresently disclosed embodiments.

FIG. 16 provides a flow chart representation of a method for dynamicallyvarying light flux over a scanned field of view of a LIDAR system,according to presently disclosed embodiments.

FIG. 17 is a flowchart illustrating an example method for alteringsensor sensitivity in a LIDAR system consistent with some embodiments ofthe present disclosure.

FIG. 18 is a diagram illustrating an example of received signals with afunction for estimating expected signals consistent with someembodiments of the present disclosure.

FIG. 19 is a diagram illustrating an example of received signals with afunction for estimating noise consistent with some embodiments of thepresent disclosure.

FIG. 20 is a flow chart illustrating a first example of method fordetecting objects in a region of interest using a LIDAR system.

FIG. 21 is a flow chart illustrating a second example of method fordetecting objects in a region of interest using a LIDAR system.

FIG. 22 is another diagram illustrating an exemplary LIDAR systemconsistent with disclosed embodiments.

FIG. 23 is a diagrammatic illustration of a LIDAR system consistent withembodiments of the present disclosure.

FIG. 24 is a flow chart of an exemplary process for controlling lightemissions consistent with embodiments of the present disclosure.

FIG. 25A is a flow chart of an exemplary implementation of the processillustrated by FIG. 24, consistent with embodiments of the presentdisclosure.

FIG. 25B is a flow chart illustrating an example method for detectingobjects, consistent with some embodiments of the present disclosure.

FIG. 26A is a flowchart illustrating an example method for detectingobjects using a LIDAR consistent with some embodiments of the presentdisclosure.

FIG. 26B is a flowchart illustrating another example method fordetecting objects using a LIDAR consistent with some embodiments of thepresent disclosure.

FIG. 26C is a flowchart illustrating yet another example method fordetecting objects using a LIDAR consistent with some embodiments of thepresent disclosure.

FIG. 27 is a diagram of a LIDAR system having a plurality of lightsources and a common deflector consistent with some embodiments of thepresent disclosure.

FIG. 28 is a diagram of another LIDAR system having a plurality of lightsources and a common deflector consistent with some embodiments of thepresent disclosure.

FIG. 29 provides a block diagram representation of a LIDAR system 100along with various sources of information that LIDAR system 100 may relyupon in apportioning an available optical budget and/or computationalbudget.

FIG. 30A provides a flow chart providing an example of a method 3000 forcontrolling a LIDAR system based on apportioned budgets consistent withthe disclosed embodiments.

FIG. 30B provides a flow chart representation of an exemplary method forcontrolling a LIDAR system according to the presently disclosedembodiments.

FIG. 31 provides a diagrammatic example of a situation that may justifyapportionment of an optical budget in a non-uniform manner consistentwith presently disclosed embodiments.

FIG. 32A-32G are a diagrams illustrating a vehicle in accordance withexemplary disclosed embodiments, the vibration compensation system, asteering device, a central processing unit (CPU), actuator-mirror, dualaxis mems mirror, single axis mems mirror, and a round mems mirror inaccordance with some embodiments.

FIG. 33 is a diagrammatic illustration of a LIDAR system installationcapable of compensating for sensed motion along a road, consistent withexemplary disclosed embodiments.

FIG. 34 is a flow diagram illustrating the method utilizing the vehiclevibration compensation system.

FIG. 35A-35D are diagrammatic representations of different detectionranges in different sectors, consistent with presently disclosedembodiments.

FIG. 36 is diagram illustrating different sectors in a field of view,consistent with presently disclosed embodiments.

FIG. 37 is a flow chart illustrating an example of a method fordetecting objects in a region of interest using a LIDAR system,consistent with presently disclosed embodiments.

FIG. 38 is a diagrammatic illustration of a field of view of a LIDARsystem consistent with embodiments of the present disclosure.

FIG. 39 is a diagrammatic illustration of an exemplary field of view ofa LIDAR system consistent with embodiments of the present disclosure.

FIGS. 40A and 40B are flow charts of an exemplary implementation of ascanning process, consistent with embodiments of the present disclosure.

FIG. 41A is a flowchart illustrating an example method for detectingobjects in a path of a vehicle using LIDAR consistent with someembodiments of the present disclosure.

FIG. 41B is a flowchart illustrating another example method fordetecting objects in a path of a vehicle using LIDAR consistent withsome embodiments of the present disclosure.

FIG. 42A is a diagram illustrating an example of a vehicle in an urbanenvironment consistent with some embodiments of the present disclosure.

FIG. 42B is a diagram illustrating an example of a vehicle in a ruralenvironment consistent with some embodiments of the present disclosure.

FIG. 42C is a diagram illustrating an example of a vehicle in a trafficjam consistent with some embodiments of the present disclosure.

FIG. 42D is a diagram illustrating an example of a vehicle in a tunnelconsistent with some embodiments of the present disclosure.

FIG. 42E is a diagram illustrating an example of a vehicle exiting atunnel consistent with some embodiments of the present disclosure.

FIG. 42F is a diagram illustrating the example vehicles of FIGS. 42A,42B, and 42C from a different angle consistent with some embodiments ofthe present disclosure.

FIG. 43 is a diagram illustrating an example LIDAR system having aplurality of light sources aimed at a common area of at least one lightdeflector.

FIG. 44 is a flowchart illustrating an example method for a LIDARdetection scheme for cross traffic turns consistent with someembodiments of the present disclosure.

FIG. 45 is a diagram illustrating an example of a LIDAR detectionscanning scheme consistent with some embodiments of the presentdisclosure.

FIGS. 46A and 46B are diagrams illustrating an example of LIDARdetection schemes for cross traffic turns and other situationsconsistent with some embodiments of the present disclosure.

FIG. 47 provides a diagrammatic illustration of a vehicle travelling ina highway environment with the assistance of a LIDAR system consistentwith exemplary disclosed embodiments.

FIGS. 48A-48D provide diagrammatic illustrations of dynamic lightallocation by a LIDAR system in a highway environment according toexemplary disclosed embodiments.

FIG. 49 illustrates a method for detecting objects in a path of avehicle using a LIDAR consistent with exemplary disclosed embodiments.

FIG. 50 is a diagram illustrating an example of a sensing arrangementfor a LIDAR system according to exemplary disclosed embodiments.

FIG. 51 is a diagrammatic illustration representing different portionsof a LIDAR field of view.

FIG. 52 is a flow chart illustrating an example of a method fordetecting objects in a region of interest using a LIDAR system.

FIG. 53 is a diagrammatic illustration of a LIDAR system consistent withembodiments of the present disclosure.

FIG. 54 is a flow chart of an exemplary implementation of a temperaturereduction process, consistent with embodiments of the presentdisclosure.

FIG. 55 is a flow chart of an exemplary implementation of a temperaturereduction process, consistent with embodiments of the presentdisclosure.

FIGS. 56-84 are diagrams illustrating various examples of MEMS mirrorsand associated components incorporated in scanning units of the LIDARsystem in accordance with some embodiments of the present disclosure.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.Wherever possible, the same reference numbers are used in the drawingsand the following description to refer to the same or similar parts.While several illustrative embodiments are described herein,modifications, adaptations and other implementations are possible. Forexample, substitutions, additions or modifications may be made to thecomponents illustrated in the drawings, and the illustrative methodsdescribed herein may be modified by substituting, reordering, removing,or adding steps to the disclosed methods. Accordingly, the followingdetailed description is not limited to the disclosed embodiments andexamples. Instead, the proper scope is defined by the appended claims.

Terms Definitions

Disclosed embodiments may involve an optical system. As used herein, theterm “optical system” broadly includes any system that is used for thegeneration, detection and/or manipulation of light. By way of exampleonly, an optical system may include one or more optical components forgenerating, detecting and/or manipulating light. For example, lightsources, lenses, mirrors, prisms, beam splitters, collimators,polarizing optics, optical modulators, optical switches, opticalamplifiers, optical detectors, optical sensors, fiber optics,semiconductor optic components, while each not necessarily required, mayeach be part of an optical system. In addition to the one or moreoptical components, an optical system may also include other non-opticalcomponents such as electrical components, mechanical components,chemical reaction components, and semiconductor components. Thenon-optical components may cooperate with optical components of theoptical system. For example, the optical system may include at least oneprocessor for analyzing detected light.

Consistent with the present disclosure, the optical system may be aLIDAR system. As used herein, the term “LIDAR system” broadly includesany system which can determine values of parameters indicative of adistance between a pair of tangible objects based on reflected light. Inone embodiment, the LIDAR system may determine a distance between a pairof tangible objects based on reflections of light emitted by the LIDARsystem. As used herein, the term “determine distances” broadly includesgenerating outputs which are indicative of distances between pairs oftangible objects. The determined distance may represent the physicaldimension between a pair of tangible objects. By way of example only,the determined distance may include a line of flight distance betweenthe LIDAR system and another tangible object in a field of view of theLIDAR system. In another embodiment, the LIDAR system may determine therelative velocity between a pair of tangible objects based onreflections of light emitted by the LIDAR system. Examples of outputsindicative of the distance between a pair of tangible objects include: anumber of standard length units between the tangible objects (e.g.number of meters, number of inches, number of kilometers, number ofmillimeters), a number of arbitrary length units (e.g. number of LIDARsystem lengths), a ratio between the distance to another length (e.g. aratio to a length of an object detected in a field of view of the LIDARsystem), an amount of time (e.g. given as standard unit, arbitrary unitsor ratio, for example, the time it takes light to travel between thetangible objects), one or more locations (e.g. specified using an agreedcoordinate system, specified in relation to a known location), and more.

The LIDAR system may determine the distance between a pair of tangibleobjects based on reflected light. In one embodiment, the LIDAR systemmay process detection results of a sensor which creates temporalinformation indicative of a period of time between the emission of alight signal and the time of its detection by the sensor. The period oftime is occasionally referred to as “time of flight” of the lightsignal. In one example, the light signal may be a short pulse, whoserise and/or fall time may be detected in reception. Using knowninformation about the speed of light in the relevant medium (usuallyair), the information regarding the time of flight of the light signalcan be processed to provide the distance the light signal traveledbetween emission and detection. In another embodiment, the LIDAR systemmay determine the distance based on frequency phase-shift (or multiplefrequency phase-shift). Specifically, the LIDAR system may processinformation indicative of one or more modulation phase shifts (e.g. bysolving some simultaneous equations to give a final measure) of thelight signal. For example, the emitted optical signal may be modulatedwith one or more constant frequencies. The at least one phase shift ofthe modulation between the emitted signal and the detected reflectionmay be indicative of the distance the light traveled between emissionand detection. The modulation may be applied to a continuous wave lightsignal, to a quasi-continuous wave light signal, or to another type ofemitted light signal. It is noted that additional information may beused by the LIDAR system for determining the distance, e.g. locationinformation (e.g. relative positions) between the projection location,the detection location of the signal (especially if distanced from oneanother), and more.

In some embodiments, the LIDAR system may be used for detecting aplurality of objects in an environment of the LIDAR system. The term“detecting an object in an environment of the LIDAR system” broadlyincludes generating information which is indicative of an object thatreflected light toward a detector associated with the LIDAR system. Ifmore than one object is detected by the LIDAR system, the generatedinformation pertaining to different objects may be interconnected, forexample a car is driving on a road, a bird is sitting on the tree, a mantouches a bicycle, a van moves towards a building. The dimensions of theenvironment in which the LIDAR system detects objects may vary withrespect to implementation. For example, the LIDAR system may be used fordetecting a plurality of objects in an environment of a vehicle on whichthe LIDAR system is installed, up to a horizontal distance of 100 m (or200 m, 300 m, etc.), and up to a vertical distance of 10 m (or 25 m, 50m, etc.). In another example, the LIDAR system may be used for detectinga plurality of objects in an environment of a vehicle or within apredefined horizontal range (e.g., 25°, 50°, 100°, 180°, etc.), and upto a predefined vertical elevation (e.g., ±10°, ±20°, +40°−20°, ±90° or0°−90°).

As used herein, the term “detecting an object” may broadly refer todetermining an existence of the object (e.g., an object may exist in acertain direction with respect to the LIDAR system and/or to anotherreference location, or an object may exist in a certain spatial volume).Additionally or alternatively, the term “detecting an object” may referto determining a distance between the object and another location (e.g.a location of the LIDAR system, a location on earth, or a location ofanother object). Additionally or alternatively, the term “detecting anobject” may refer to identifying the object (e.g. classifying a type ofobject such as car, plant, tree, road; recognizing a specific object(e.g., the Washington Monument); determining a license plate number;determining a composition of an object (e.g., solid, liquid,transparent, semitransparent); determining a kinematic parameter of anobject (e.g., whether it is moving, its velocity, its movementdirection, expansion of the object). Additionally or alternatively, theterm “detecting an object” may refer to generating a point cloud map inwhich every point of one or more points of the point cloud mapcorrespond to a location in the object or a location on a face thereof.In one embodiment, the data resolution associated with the point cloudmap representation of the field of view may be associated with 0.1°×0.1°or 0.3°×0.3° of the field of view.

Consistent with the present disclosure, the term “object” broadlyincludes a finite composition of matter that may reflect light from atleast a portion thereof. For example, an object may be at leastpartially solid (e.g. cars, trees); at least partially liquid (e.g.puddles on the road, rain); at least partly gaseous (e.g. fumes,clouds); made from a multitude of distinct particles (e.g. sand storm,fog, spray); and may be of one or more scales of magnitude, such as ˜1millimeter (mm), ˜5 mm, ˜10 mm, ˜50 mm, ˜100 mm, ˜500 mm, ˜1 meter (m),˜5 m, ˜10 m, ˜50 m, ˜100 m, and so on. Smaller or larger objects, aswell as any size in between those examples, may also be detected. It isnoted that for various reasons, the LIDAR system may detect only part ofthe object. For example, in some cases, light may be reflected from onlysome sides of the object (e.g., only the side opposing the LIDAR systemwill be detected); in other cases, light may be projected on only partof the object (e.g. laser beam projected onto a road or a building); inother cases, the object may be partly blocked by another object betweenthe LIDAR system and the detected object; in other cases, the LIDAR'ssensor may only detects light reflected from a portion of the object,e.g., because ambient light or other interferences interfere withdetection of some portions of the object.

Consistent with the present disclosure, a LIDAR system may be configuredto detect objects by scanning the environment of LIDAR system. The term“scanning the environment of LIDAR system” broadly includes illuminatingthe field of view or a portion of the field of view of the LIDAR system.In one example, scanning the environment of LIDAR system may be achievedby moving or pivoting a light deflector to deflect light in differingdirections toward different parts of the field of view. In anotherexample, scanning the environment of LIDAR system may be achieved bychanging a positioning (i.e. location and/or orientation) of a sensorwith respect to the field of view. In another example, scanning theenvironment of LIDAR system may be achieved by changing a positioning(i.e. location and/or orientation) of a light source with respect to thefield of view. In yet another example, scanning the environment of LIDARsystem may be achieved by changing the positions of at least one lightsource and of at least one sensor to move rigidly respect to the fieldof view (i.e. the relative distance and orientation of the at least onesensor and of the at least one light source remains).

As used herein the term “field of view of the LIDAR system” may broadlyinclude an extent of the observable environment of LIDAR system in whichobjects may be detected. It is noted that the field of view (FOV) of theLIDAR system may be affected by various conditions such as but notlimited to: an orientation of the LIDAR system (e.g. is the direction ofan optical axis of the LIDAR system); a position of the LIDAR systemwith respect to the environment (e.g. distance above ground and adjacenttopography and obstacles); operational parameters of the LIDAR system(e.g. emission power, computational settings, defined angles ofoperation), etc. The field of view of LIDAR system may be defined, forexample, by a solid angle (e.g. defined using ϕ, θ angles, in which ϕand θ are angles defined in perpendicular planes, e.g. with respect tosymmetry axes of the LIDAR system and/or its FOV). In one example, thefield of view may also be defined within a certain range (e.g. up to 200m).

Similarly, the term “instantaneous field of view” may broadly include anextent of the observable environment in which objects may be detected bythe LIDAR system at any given moment. For example, for a scanning LIDARsystem, the instantaneous field of view is narrower than the entire FOVof the LIDAR system, and it can be moved within the FOV of the LIDARsystem in order to enable detection in other parts of the FOV of theLIDAR system. The movement of the instantaneous field of view within theFOV of the LIDAR system may be achieved by moving a light deflector ofthe LIDAR system (or external to the LIDAR system), so as to deflectbeams of light to and/or from the LIDAR system in differing directions.In one embodiment, LIDAR system may be configured to scan scene in theenvironment in which the LIDAR system is operating. As used herein theterm “scene” may broadly include some or all of the objects within thefield of view of the LIDAR system, in their relative positions and intheir current states, within an operational duration of the LIDARsystem. For example, the scene may include ground elements (e.g. earth,roads, grass, sidewalks, road surface marking), sky, man-made objects(e.g. vehicles, buildings, signs), vegetation, people, animals, lightprojecting elements (e.g. flashlights, sun, other LIDAR systems), and soon.

Disclosed embodiments may involve obtaining information for use ingenerating reconstructed three-dimensional models. Examples of types ofreconstructed three-dimensional models which may be used include pointcloud models, and Polygon Mesh (e.g. a triangle mesh). The terms “pointcloud” and “point cloud model” are widely known in the art, and shouldbe construed to include a set of data points located spatially in somecoordinate system (i.e., having an identifiable location in a spacedescribed by a respective coordinate system). The term “point cloudpoint” refer to a point in space (which may be dimensionless, or aminiature cellular space, e.g. 1 cm³), and whose location may bedescribed by the point cloud model using a set of coordinates (e.g.(X,Y,Z), (r,ϕ,θ)). By way of example only, the point cloud model maystore additional information for some or all of its points (e.g. colorinformation for points generated from camera images). Likewise, anyother type of reconstructed three-dimensional model may store additionalinformation for some or all of its objects. Similarly, the terms“polygon mesh” and “triangle mesh” are widely known in the art, and areto be construed to include, among other things, a set of vertices, edgesand faces that define the shape of one or more 3D objects (such as apolyhedral object). The faces may include one or more of the following:triangles (triangle mesh), quadrilaterals, or other simple convexpolygons, since this may simplify rendering. The faces may also includemore general concave polygons, or polygons with holes. Polygon meshesmay be represented using differing techniques, such as: Vertex-vertexmeshes. Face-vertex meshes, Winged-edge meshes and Render dynamicmeshes. Different portions of the polygon mesh (e.g., vertex, face,edge) are located spatially in some coordinate system (i.e., having anidentifiable location in a space described by the respective coordinatesystem), either directly and/or relative to one another. The generationof the reconstructed three-dimensional model may be implemented usingany standard, dedicated and/or novel photogrammetry technique, many ofwhich are known in the art. It is noted that other types of models ofthe environment may be generated by the LIDAR system.

Consistent with disclosed embodiments, the LIDAR system may include atleast one projecting unit with a light source configured to projectlight. As used herein the term “light source” broadly refers to anydevice configured to emit light. In one embodiment, the light source maybe a laser such as a solid-state laser, laser diode, a high power laser,or an alternative light source such as, a light emitting diode(LED)-based light source. In addition, light source 112 as illustratedthroughout the figures, may emit light in differing formats, such aslight pulses, continuous wave (CW), quasi-CW, and so on. For example,one type of light source that may be used is a vertical-cavitysurface-emitting laser (VCSEL). Another type of light source that may beused is an external cavity diode laser (ECDL). In some examples, thelight source may include a laser diode configured to emit light at awavelength between about 650 nm and 1150 nm. Alternatively, the lightsource may include a laser diode configured to emit light at awavelength between about 800 nm and about 1000 nm, between about 850 nmand about 950 nm, or between about 1300 nm and about 1600 nm. Unlessindicated otherwise, the term “about” with regards to a numeric value isdefined as a variance of up to 5% with respect to the stated value.Additional details on the projecting unit and the at least one lightsource are described below with reference to FIGS. 2A-2C.

Consistent with disclosed embodiments, the LIDAR system may include atleast one scanning unit with at least one light deflector configured todeflect light from the light source in order to scan the field of view.The term “light deflector” broadly includes any mechanism or modulewhich is configured to make light deviate from its original path; forexample, a mirror, a prism, controllable lens, a mechanical mirror,mechanical scanning polygons, active diffraction (e.g. controllableLCD). Risley prisms, non-mechanical-electro-optical beam steering (suchas made by Vscent), polarization grating (such as offered by BoulderNon-Linear Systems), optical phased array (OPA), and more. In oneembodiment, a light deflector may include a plurality of opticalcomponents, such as at least one reflecting element (e.g. a mirror), atleast one refracting element (e.g. a prism, a lens), and so on. In oneexample, the light deflector may be movable, to cause light deviate todiffering degrees (e.g. discrete degrees, or over a continuous span ofdegrees). The light deflector may optionally be controllable indifferent ways (e.g. deflect to a degree α, change deflection angle byΔα, move a component of the light deflector by M millimeters, changespeed in which the deflection angle changes). In addition, the lightdeflector may optionally be operable to change an angle of deflectionwithin a single plane (e.g., θ coordinate). The light deflector mayoptionally be operable to change an angle of deflection within twonon-parallel planes (e.g., θ and ϕ coordinates). Alternatively or inaddition, the light deflector may optionally be operable to change anangle of deflection between predetermined settings (e.g. along apredefined scanning route) or otherwise. With respect the use of lightdeflectors in LIDAR systems, it is noted that a light deflector may beused in the outbound direction (also referred to as transmissiondirection, or TX) to deflect light from the light source to at least apart of the field of view. However, a light deflector may also be usedin the inbound direction (also referred to as reception direction, orRX) to deflect light from at least a part of the field of view to one ormore light sensors. Additional details on the scanning unit and the atleast one light deflector are described below with reference to FIGS.3A-3C.

Disclosed embodiments may involve pivoting the light deflector in orderto scan the field of view. As used herein the term “pivoting” broadlyincludes rotating of an object (especially a solid object) about one ormore axis of rotation, while substantially maintaining a center ofrotation fixed. In one embodiment, the pivoting of the light deflectormay include rotation of the light deflector about a fixed axis (e.g., ashaft), but this is not necessarily so. For example, in some MEMS mirrorimplementation, the MEMS mirror may move by actuation of a plurality ofbenders connected to the mirror, the mirror may experience some spatialtranslation in addition to rotation. Nevertheless, such mirror may bedesigned to rotate about a substantially fixed axis, and thereforeconsistent with the present disclosure it considered to be pivoted. Inother embodiments, some types of light deflectors (e.g.non-mechanical-electro-optical beam steering, OPA) do not require anymoving components or internal movements in order to change thedeflection angles of deflected light. It is noted that any discussionrelating to moving or pivoting a light deflector is also mutatismutandis applicable to controlling the light deflector such that itchanges a deflection behavior of the light deflector. For example,controlling the light deflector may cause a change in a deflection angleof beams of light arriving from at least one direction.

Disclosed embodiments may involve receiving reflections associated witha portion of the field of view corresponding to a single instantaneousposition of the light deflector. As used herein, the term “instantaneousposition of the light deflector” (also referred to as “state of thelight deflector”) broadly refers to the location or position in spacewhere at least one controlled component of the light deflector issituated at an instantaneous point in time, or over a short span oftime. In one embodiment, the instantaneous position of light deflectormay be gauged with respect to a frame of reference. The frame ofreference may pertain to at least one fixed point in the LIDAR system.Or, for example, the frame of reference may pertain to at least onefixed point in the scene. In some embodiments, the instantaneousposition of the light deflector may include some movement of one or morecomponents of the light deflector (e.g. mirror, prism), usually to alimited degree with respect to the maximal degree of change during ascanning of the field of view. For example, a scanning of the entire thefield of view of the LIDAR system may include changing deflection oflight over a span of 30°, and the instantaneous position of the at leastone light deflector may include angular shifts of the light deflectorwithin 0.05°. In other embodiments, the term “instantaneous position ofthe light deflector” may refer to the positions of the light deflectorduring acquisition of light which is processed to provide data for asingle point of a point cloud (or another type of 3D model) generated bythe LIDAR system. In some embodiments, an instantaneous position of thelight deflector may correspond with a fixed position or orientation inwhich the deflector pauses for a short time during illumination of aparticular sub-region of the LIDAR field of view. In other cases, aninstantaneous position of the light deflector may correspond with acertain position/orientation along a scanned range ofpositions/orientations of the light deflector that the light deflectorpasses through as part of a continuous or semi-continuous scan of theLIDAR field of view. In some embodiments, the light deflector may bemoved such that during a scanning cycle of the LIDAR FOV the lightdeflector is located at a plurality of different instantaneouspositions. In other words, during the period of time in which a scanningcycle occurs, the deflector may be moved through a series of differentinstantaneous positions/orientations, and the deflector may reach eachdifferent instantaneous position/orientation at a different time duringthe scanning cycle.

Consistent with disclosed embodiments, the LIDAR system may include atleast one sensing unit with at least one sensor configured to detectreflections from objects in the field of view. The term “sensor” broadlyincludes any device, element, or system capable of measuring properties(e.g., power, frequency, phase, pulse timing, pulse duration) ofelectromagnetic waves and to generate an output relating to the measuredproperties. In some embodiments, the at least one sensor may include aplurality of detectors constructed from a plurality of detectingelements. The at least one sensor may include light sensors of one ormore types. It is noted that the at least one sensor may includemultiple sensors of the same type which may differ in othercharacteristics (e.g., sensitivity, size). Other types of sensors mayalso be used. Combinations of several types of sensors can be used fordifferent reasons, such as improving detection over a span of ranges(especially in close range); improving the dynamic range of the sensor;improving the temporal response of the sensor; and improving detectionin varying environmental conditions (e.g. atmospheric temperature, rain,etc.).

In one embodiment, the at least one sensor includes a SiPM (Siliconphotomultipliers) which is a solid-state single-photon-sensitive devicebuilt from an array of avalanche photodiode (APD), single photonavalanche diode (SPAD), serving as detection elements on a commonsilicon substrate. In one example, a typical distance between SPADs maybe between about 10 μm and about 50 μm, wherein each SPAD may have arecovery time of between about 20 ns and about 100 ns. Similarphotomultipliers from other, non-silicon materials may also be used.Although a SiPM device works in digital/switching mode, the SiPM is ananalog device because all the microcells may be read in parallel, makingit possible to generate signals within a dynamic range from a singlephoton to hundreds and thousands of photons detected by the differentSPADs. It is noted that outputs from different types of sensors (e.g.,SPAD, APD, SiPM, PIN diode, Photodetector) may be combined together to asingle output which may be processed by a processor of the LIDAR system.Additional details on the sensing unit and the at least one sensor aredescribed below with reference to FIGS. 4A-4C.

Consistent with disclosed embodiments, the LIDAR system may include orcommunicate with at least one processor configured to execute differingfunctions. The at least one processor may constitute any physical devicehaving an electric circuit that performs a logic operation on input orinputs. For example, the at least one processor may include one or moreintegrated circuits (IC), including Application-specific integratedcircuit (ASIC), microchips, microcontrollers, microprocessors, all orpart of a central processing unit (CPU), graphics processing unit (GPU),digital signal processor (DSP), field-programmable gate array (FPGA), orother circuits suitable for executing instructions or performing logicoperations. The instructions executed by at least one processor may, forexample, be pre-loaded into a memory integrated with or embedded intothe controller or may be stored in a separate memory. The memory maycomprise a Random Access Memory (RAM), a Read-Only Memory (ROM), a harddisk, an optical disk, a magnetic medium, a flash memory, otherpermanent, fixed, or volatile memory, or any other mechanism capable ofstoring instructions. In some embodiments, the memory is configured tostore information representative data about objects in the environmentof the LIDAR system. In some embodiments, the at least one processor mayinclude more than one processor. Each processor may have a similarconstruction or the processors may be of differing constructions thatare electrically connected or disconnected from each other. For example,the processors may be separate circuits or integrated in a singlecircuit. When more than one processor is used, the processors may beconfigured to operate independently or collaboratively. The processorsmay be coupled electrically, magnetically, optically, acoustically,mechanically or by other means that permit them to interact. Additionaldetails on the processing unit and the at least one processor aredescribed below with reference to FIGS. 5A-5C.

System Overview

FIG. 1A illustrates a LIDAR system 100 including a projecting unit 102,a scanning unit 104, a sensing unit 106, and a processing unit 108.LIDAR system 100 may be mountable on a vehicle 110. Consistent withembodiments of the present disclosure, projecting unit 102 may includeat least one light source 112, scanning unit 104 may include at leastone light deflector 114, sensing unit 106 may include at least onesensor 116, and processing unit 108 may include at least one processor118. In one embodiment, at least one processor 118 may be configured tocoordinate operation of the at least one light source 112 with themovement of at least one light deflector 114 in order to scan a field ofview 120. During a scanning cycle, each instantaneous position of atleast one light deflector 114 may be associated with a particularportion 122 of field of view 120. In addition, LIDAR system 100 mayinclude at least one optional optical window 124 for directing lightprojected towards field of view 120 and/or receiving light reflectedfrom objects in field of view 120. Optional optical window 124 may servedifferent purposes, such as collimation of the projected light andfocusing of the reflected light. In one embodiment, optional opticalwindow 124 may be an opening, a flat window, a lens, or any other typeof optical window.

Consistent with the present disclosure, LIDAR system 100 may be used inautonomous or semi-autonomous road-vehicles (for example, cars, buses,vans, trucks and any other terrestrial vehicle). Autonomousroad-vehicles with LIDAR system 100 may scan their environment and driveto a destination vehicle without human input. Similarly, LIDAR system100 may also be used in autonomous/semi-autonomous aerial-vehicles (forexample, UAV, drones, quadcopters, and any other airborne vehicle ordevice); or in an autonomous or semi-autonomous water vessel (e.g.,boat, ship, submarine, or any other watercraft). Autonomousaerial-vehicles and water craft with LIDAR system 100 may scan theirenvironment and navigate to a destination autonomously or using a remotehuman operator. According to one embodiment, vehicle 110 (either aroad-vehicle, aerial-vehicle, or watercraft) may use LIDAR system 100 toaid in detecting and scanning the environment in which vehicle 110 isoperating.

In some embodiments, LIDAR system 100 may include one or more scanningunits 104 to scan the environment around vehicle 110. LIDAR system 100may be attached or mounted to any part of vehicle 110. Sensing unit 106may receive reflections from the surroundings of vehicle 110, andtransfer reflections signals indicative of light reflected from objectsin field of view 120 to processing unit 108. Consistent with the presentdisclosure, scanning units 104 may be mounted to or incorporated into abumper, a fender, a side panel, a spoiler, a roof, a headlight assembly,a taillight assembly, a rear-view mirror assembly, a hood, a trunk orany other suitable part of vehicle 110 capable of housing at least aportion of the LIDAR system. In some cases, LIDAR system 100 may capturea complete surround view of the environment of vehicle 110. Thus, LIDARsystem 100 may have a 360-degree horizontal field of view. In oneexample, as shown in FIG. 1A, LIDAR system 100 may include a singlescanning unit 104 mounted on a roof vehicle 110. Alternatively, LIDARsystem 100 may include multiple scanning units (e.g., two, three, four,or more scanning units 104) each with a field of few such that in theaggregate the horizontal field of view is covered by a 360-degree scanaround vehicle 110. One skilled in the art will appreciate that LIDARsystem 100 may include any number of scanning units 104 arranged in anymanner, each with an 80° to 120° field of view or less, depending on thenumber of units employed. Moreover, a 360-degree horizontal field ofview may be also obtained by mounting a multiple LIDAR systems 100 onvehicle 110, each with a single scanning unit 104. It is neverthelessnoted, that the one or more LIDAR systems 100 do not have to provide acomplete 360° field of view, and that narrower fields of view may beuseful in some situations. For example, vehicle 110 may require a firstLIDAR system 100 having an field of view of 75° looking ahead of thevehicle, and possibly a second LIDAR system 100 with a similar FOVlooking backward (optionally with a lower detection range). It is alsonoted that different vertical field of view angles may also beimplemented.

FIG. 1B is an image showing an exemplary output from a single scanningcycle of LIDAR system 100 mounted on vehicle 110 consistent withdisclosed embodiments. In this example, scanning unit 104 isincorporated into a right headlight assembly of vehicle 110. Every graydot in the image corresponds to a location in the environment aroundvehicle 110 determined from reflections detected by sensing unit 106. Inaddition to location, each gray dot may also be associated withdifferent types of information, for example, intensity (e.g., how muchlight returns back from that location), reflectivity, proximity to otherdots, and more. In one embodiment, LIDAR system 100 may generate aplurality of point-cloud data entries from detected reflections ofmultiple scanning cycles of the field of view to enable, for example,determining a point cloud model of the environment around vehicle 110.

FIG. 1C is an image showing a representation of the point cloud modeldetermined from the output of LIDAR system 100. Consistent withdisclosed embodiments, by processing the generated point-cloud dataentries of the environment around vehicle 110, a surround-view image maybe produced from the point cloud model. In one embodiment, the pointcloud model may be provided to a feature extraction module, whichprocesses the point cloud information to identify a plurality offeatures. Each feature may include data about different aspects of thepoint cloud and/or of objects in the environment around vehicle 110(e.g. cars, trees, people, and roads). Features may have the sameresolution of the point cloud model (i.e. having the same number of datapoints, optionally arranged into similar sized 2D arrays), or may havedifferent resolutions. The features may be stored in any kind of datastructure (e.g. raster, vector, 2D array, 1D array). In addition,virtual features, such as a representation of vehicle 110, border lines,or bounding boxes separating regions or objects in the image (e.g., asdepicted in FIG. 1B), and icons representing one or more identifiedobjects, may be overlaid on the representation of the point cloud modelto form the final surround-view image. For example, a symbol of vehicle110 may be overlaid at a center of the surround-view image.

The Projecting Unit

FIGS. 2A-2D depict various configurations of projecting unit 102 and itsrole in LIDAR system 100. Specifically, FIG. 2A is a diagramillustrating projecting unit 102 with a single light source, FIG. 2B isa diagram illustrating a plurality of projecting units 102 with aplurality of light sources aimed at a common light deflector 114, FIG.2C is a diagram illustrating projecting unit 102 with a primary and asecondary light sources 112, and FIG. 2D is a diagram illustrating anasymmetrical deflector used in some configurations of projecting unit102. One skilled in the art will appreciate that the depictedconfigurations of projecting unit 102 may have numerous variations andmodifications.

FIG. 2A illustrates an example of a bi-static configuration of LIDARsystem 100 in which projecting unit 102 includes a single light source112. The term “bi-static configuration” broadly refers to LIDAR systemsconfigurations in which the projected light exiting the LIDAR system andthe reflected light entering the LIDAR system pass through differentoptical channels. Specifically, the outbound light radiation may passthrough a first optical window (not shown) and the inbound lightradiation may pass through another optical window (not shown). In theexample depicted in FIG. 2A, the Bi-static configuration includes aconfiguration where scanning unit 104 includes two light deflectors, afirst light deflector 114A for outbound light and a second lightdeflector 114B for inbound light (the inbound light in LIDAR systemincludes emitted light reflected from objects in the scene, and may alsoinclude ambient light arriving from other sources). In such aconfiguration the inbound and outbound paths differ.

In this embodiment, all the components of LIDAR system 100 may becontained within a single housing 200, or may be divided among aplurality of housings. As shown, projecting unit 102 is associated witha single light source 112 that includes a laser diode 202A (or one ormore laser diodes coupled together) configured to emit light (projectedlight 204). In one non limiting example, the light projected by lightsource 112 may be at a wavelength between about 800 nm and 950 nm, havean average power between about 50 mW and about 500 mW, have a peak powerbetween about 50 W and about 200 W. and a pulse width of between about 2ns and about 100 ns. In addition, light source 112 may optionally beassociated with optical assembly 202B used for manipulation of the lightemitted by laser diode 202A (e.g. for collimation, focusing, etc.). Itis noted that other types of light sources 112 may be used, and that thedisclosure is not restricted to laser diodes. In addition, light source112 may emit its light in different formats, such as light pulses,frequency modulated, continuous wave (CW), quasi-CW, or any other formcorresponding to the particular light source employed. The projectionformat and other parameters may be changed by the light source from timeto time based on different factors, such as instructions from processingunit 108. The projected light is projected towards an outbound deflector114A that functions as a steering element for directing the projectedlight in field of view 120. In this example, scanning unit 104 alsoinclude a pivotable return deflector 114B that direct photons (reflectedlight 206) reflected back from an object 208 within field of view 120toward sensor 116. The reflected light is detected by sensor 116 andinformation about the object (e.g., the distance to object 212) isdetermined by processing unit 108.

In this figure, LIDAR system 100 is connected to a host 210. Consistentwith the present disclosure, the term “host” refers to any computingenvironment that may interface with LIDAR system 100, it may be avehicle system (e.g., part of vehicle 110), a testing system, a securitysystem, a surveillance system, a traffic control system, an urbanmodelling system, or any system that monitors its surroundings. Suchcomputing environment may include at least one processor and/or may beconnected LIDAR system 100 via the cloud. In some embodiments, host 210may also include interfaces to external devices such as camera andsensors configured to measure different characteristics of host 210(e.g., acceleration, steering wheel deflection, reverse drive, etc.).Consistent with the present disclosure, LIDAR system 100 may be fixed toa stationary object associated with host 210 (e.g. a building, a tripod)or to a portable system associated with host 210 (e.g., a portablecomputer, a movie camera). Consistent with the present disclosure, LIDARsystem 100 may be connected to host 210, to provide outputs of LIDARsystem 100 (e.g., a 3D model, a reflectivity image) to host 210.Specifically, host 210 may use LIDAR system 100 to aid in detecting andscanning the environment of host 210 or any other environment. Inaddition, host 210 may integrate, synchronize or otherwise use togetherthe outputs of LIDAR system 100 with outputs of other sensing systems(e.g. cameras, microphones, radar systems). In one example, LIDAR system100 may be used by a security system. This embodiment is described ingreater detail below with reference to FIG. 7.

LIDAR system 100 may also include a bus 212 (or other communicationmechanisms) that interconnect subsystems and components for transferringinformation within LIDAR system 100. Optionally, bus 212 (or anothercommunication mechanism) may be used for interconnecting LIDAR system100 with host 210. In the example of FIG. 2A, processing unit 108includes two processors 118 to regulate the operation of projecting unit102, scanning unit 104, and sensing unit 106 in a coordinated mannerbased, at least partially, on information received from internalfeedback of LIDAR system 100. In other words, processing unit 108 may beconfigured to dynamically operate LIDAR system 100 in a closed loop. Aclosed loop system is characterized by having feedback from at least oneof the elements and updating one or more parameters based on thereceived feedback. Moreover, a closed loop system may receive feedbackand update its own operation, at least partially, based on thatfeedback. A dynamic system or element is one that may be updated duringoperation.

According to some embodiments, scanning the environment around LIDARsystem 100 may include illuminating field of view 120 with light pulses.The light pulses may have parameters such as: pulse duration, pulseangular dispersion, wavelength, instantaneous power, photon density atdifferent distances from light source 112, average power, pulse powerintensity, pulse width, pulse repetition rate, pulse sequence, pulseduty cycle, wavelength, phase, polarization, and more. Scanning theenvironment around LIDAR system 100 may also include detecting andcharacterizing various aspects of the reflected light. Characteristicsof the reflected light may include, for example: time-of-flight (i.e.,time from emission until detection), instantaneous power (e.g., powersignature), average power across entire return pulse, and photondistribution/signal over return pulse period. By comparingcharacteristics of a light pulse with characteristics of correspondingreflections, a distance and possibly a physical characteristic, such asreflected intensity of object 212 may be estimated. By repeating thisprocess across multiple adjacent portions 122, in a predefined pattern(e.g., raster, Lissajous or other patterns) an entire scan of field ofview 120 may be achieved. As discussed below in greater detail, in somesituations LIDAR system 100 may direct light to only some of theportions 122 in field of view 120 at every scanning cycle. Theseportions may be adjacent to each other, but not necessarily so.

In another embodiment, LIDAR system 100 may include network interface214 for communicating with host 210 (e.g., a vehicle controller). Thecommunication between LIDAR system 100 and host 210 is represented by adashed arrow. In one embodiment, network interface 214 may include anintegrated services digital network (ISDN) card, cable modem, satellitemodem, or a modem to provide a data communication connection to acorresponding type of telephone line. As another example, networkinterface 214 may include a local area network (LAN) card to provide adata communication connection to a compatible LAN. In anotherembodiment, network interface 214 may include an Ethernet port connectedto radio frequency receivers and transmitters and/or optical (e.g.,infrared) receivers and transmitters. The specific design andimplementation of network interface 214 depends on the communicationsnetwork(s) over which LIDAR system 100 and host 210 are intended tooperate. For example, network interface 214 may be used, for example, toprovide outputs of LIDAR system 100 to the external system, such as a 3Dmodel, operational parameters of LIDAR system 100, and so on. In otherembodiment, the communication unit may be used, for example, to receiveinstructions from the external system, to receive information regardingthe inspected environment, to receive information from another sensor,etc.

FIG. 2B illustrates an example of a monostatic configuration of LIDARsystem 100 including a plurality projecting units 102. The term“monostatic configuration” broadly refers to LIDAR systemsconfigurations in which the projected light exiting from the LIDARsystem and the reflected light entering the LIDAR system pass through atleast a partially shared optical path. In one example, the outboundlight beam and the inbound light beam may share at least one opticalassembly through which both light beams. In another example, theoutbound light radiation may pass through an optical window (not shown)and the inbound light radiation may pass through the same opticalwindow. A monostatic configuration may include a configuration where thescanning unit 104 includes a single light deflector 114 that directs theprojected light towards field of view 120 and directs the reflectedlight towards a sensor 116. As shown, both projected light 204 andreflected light 206 hits an asymmetrical deflector 216. The term“asymmetrical deflector” refers to any optical device having two sidescapable of deflecting a beam of light hitting it from one side in adifferent direction than it deflects a beam of light hitting it from thesecond side. In one example, the asymmetrical deflector does not deflectprojected light 204 and deflects reflected light 206 towards sensor 116.One example of an asymmetrical deflector may include a polarization beamsplitter. In another example, asymmetrical 216 may include an opticalisolator that allows the passage of light in only one direction.Consistent with the present disclosure, a monostatic configuration ofLIDAR system 100 may include an asymmetrical deflector to preventreflected light from hitting light source 112, and to direct all thereflected light toward sensor 116, thereby increasing detectionsensitivity.

In the embodiment of FIG. 2B, LIDAR system 100 includes three projectingunits 102 each with a single of light source 112 aimed at a common lightdeflector 114. In one embodiment, the plurality of light sources 112(including two or more light sources) may project light withsubstantially the same wavelength and each light source 112 is generallyassociated with a differing area of the field of view (denoted in thefigure as 120A, 120B, and 120C). This enables scanning of a broaderfield of view than can be achieved with a light source 112. In anotherembodiment, the plurality of light sources 102 may project light withdiffering wavelengths, and all the light sources 112 may be directed tothe same portion (or overlapping portions) of field of view 120.

FIG. 2C illustrates an example of LIDAR system 100 in which projectingunit 102 includes a primary light source 112A and a secondary lightsource 112B. Primary light source 112A may project light with a longerwavelength than is sensitive to the human eye in order to optimize SNRand detection range. For example, primary light source 112A may projectlight with a wavelength between about 750 nm and 1100 nm. In contrast,secondary light source 112B may project light with a wavelength visibleto the human eye. For example, secondary light source 112B may projectlight with a wavelength between about 400 nm and 700 nm. In oneembodiment, secondary light source 112B may project light alongsubstantially the same optical path the as light projected by primarylight source 112A. Both light sources may be time-synchronized and mayproject light emission together or in interleaved pattern. An interleavepattern means that the light sources are not active at the same timewhich may mitigate mutual interference. A person who is of skill in theart would readily see that other combinations of wavelength ranges andactivation schedules may also be implemented.

Consistent with some embodiments, secondary light source 112B may causehuman eyes to blink when it is too close to the LIDAR optical outputport. This may ensure an eye safety mechanism not feasible with typicallaser sources that utilize the near-infrared light spectrum. In anotherembodiment, secondary light source 112B may be used for calibration andreliability at a point of service, in a manner somewhat similar to thecalibration of headlights with a special reflector/pattern at a certainheight from the ground with respect to vehicle 110. An operator at apoint of service could examine the calibration of the LIDAR by simplevisual inspection of the scanned pattern over a featured target such atest pattern board at a designated distance from LIDAR system 100. Inaddition, secondary light source 112B may provide means for operationalconfidence that the LIDAR is working for the end-user. For example, thesystem may be configured to permit a human to place a hand in front oflight deflector 114 to test its operation.

Secondary light source 112B may also have a non-visible element that candouble as a backup system in case primary light source 112A fails. Thisfeature may be useful for fail-safe devices with elevated functionalsafety ratings. Given that secondary light source 112B may be visibleand also due to reasons of cost and complexity, secondary light source112B may be associated with a smaller power compared to primary lightsource 112A. Therefore, in case of a failure of primary light source112A, the system functionality will fall back to secondary light source112B set of functionalities and capabilities. While the capabilities ofsecondary light source 112B may be inferior to the capabilities ofprimary light source 112A, LIDAR system 100 system may be designed insuch a fashion to enable vehicle 110 to safely arrive its destination.

FIG. 2D illustrates asymmetrical deflector 216 that may be part of LIDARsystem 100. In the illustrated example, asymmetrical deflector 216includes a reflective surface 218 (such as a mirror) and a one-waydeflector 220. While not necessarily so, asymmetrical deflector 216 mayoptionally be a static deflector. Asymmetrical deflector 216 may be usedin a monostatic configuration of LIDAR system 100, in order to allow acommon optical path for transmission and for reception of light via theat least one deflector 114, e.g. as illustrated in FIGS. 2B and 2C.However, typical asymmetrical deflectors such as beam splitters arecharacterized by energy losses, especially in the reception path, whichmay be more sensitive to power loses than the transmission path.

As depicted in FIG. 2D, LIDAR system 100 may include asymmetricaldeflector 216 positioned in the transmission path, which includesone-way deflector 220 for separating between the transmitted andreceived light signals. Optionally, one-way deflector 220 may besubstantially transparent to the transmission light and substantiallyreflective to the received light. The transmitted light is generated byprojecting unit 102 and may travel through one-way deflector 220 toscanning unit 104 which deflects it towards the optical outlet. Thereceived light arrives through the optical inlet, to the at least onedeflecting element 114, which deflects the reflections signal into aseparate path away from the light source and towards sensing unit 106.Optionally, asymmetrical deflector 216 may be combined with a polarizedlight source 112 which is linearly polarized with the same polarizationaxis as one-way deflector 220. Notably, the cross-section of theoutbound light beam is much smaller than that of the reflectionssignals. Accordingly, LIDAR system 100 may include one or more opticalcomponents (e.g. lens, collimator) for focusing or otherwisemanipulating the emitted polarized light beam to the dimensions of theasymmetrical deflector 216. In one embodiment, one-way deflector 220 maybe a polarizing beam splitter that is virtually transparent to thepolarized light beam.

Consistent with some embodiments, LIDAR system 100 may further includeoptics 222 (e.g., a quarter wave plate retarder) for modifying apolarization of the emitted light. For example, optics 222 may modify alinear polarization of the emitted light beam to circular polarization.Light reflected back to system 100 from the field of view would arriveback through deflector 114 to optics 222, bearing a circularpolarization with a reversed handedness with respect to the transmittedlight. Optics 222 would then convert the received reversed handednesspolarization light to a linear polarization that is not on the same axisas that of the polarized beam splitter 216. As noted above, the receivedlight-patch is larger than the transmitted light-patch, due to opticaldispersion of the beam traversing through the distance to the target.

Some of the received light will impinge on one-way deflector 220 thatwill reflect the light towards sensor 106 with some power loss. However,another part of the received patch of light will fall on a reflectivesurface 218 which surrounds one-way deflector 220 (e.g., polarizing beamsplitter slit). Reflective surface 218 will reflect the light towardssensing unit 106 with substantially zero power loss. One-way deflector220 would reflect light that is composed of various polarization axesand directions that will eventually arrive at the detector. Optionally,sensing unit 106 may include sensor 116 that is agnostic to the laserpolarization, and is primarily sensitive to the amount of impingingphotons at a certain wavelength range.

It is noted that the proposed asymmetrical deflector 216 provides farsuperior performances when compared to a simple mirror with a passagehole in it. In a mirror with a hole, all of the reflected light whichreaches the hole is lost to the detector. However, in deflector 216,one-way deflector 220 deflects a significant portion of that light(e.g., about 50%) toward the respective sensor 116. In LIDAR systems,the number photons reaching the LIDAR from remote distances is verylimited, and therefore the improvement in photon capture rate isimportant.

According to some embodiments, a device for beam splitting and steeringis described. A polarized beam may be emitted from a light source havinga first polarization. The emitted beam may be directed to pass through apolarized beam splitter assembly. The polarized beam splitter assemblyincludes on a first side a one-directional slit and on an opposing sidea mirror. The one-directional slit enables the polarized emitted beam totravel toward a quarter-wave-plate/wave-retarder which changes theemitted signal from a polarized signal to a linear signal (or viceversa) so that subsequently reflected beams cannot travel through theone-directional slit.

The Scanning Unit

FIGS. 3A-3D depict various configurations of scanning unit 104 and itsrole in LIDAR system 100. Specifically, FIG. 3A is a diagramillustrating scanning unit 104 with a MEMS mirror (e.g., square shaped),FIG. 3B is a diagram illustrating another scanning unit 104 with a MEMSmirror (e.g., round shaped), FIG. 3C is a diagram illustrating scanningunit 104 with an array of reflectors used for monostatic scanning LIDARsystem, and FIG. 3D is a diagram illustrating an example LIDAR system100 that mechanically scans the environment around LIDAR system 100. Oneskilled in the art will appreciate that the depicted configurations ofscanning unit 104 are exemplary only, and may have numerous variationsand modifications within the scope of this disclosure.

FIG. 3A illustrates an example scanning unit 104 with a single axissquare MEMS mirror 300. In this example MEMS mirror 300 functions as atleast one deflector 114. As shown, scanning unit 104 may include one ormore actuators 302 (specifically, 302A and 302B). In one embodiment,actuator 302 may be made of semiconductor (e.g., silicon) and includes apiezoelectric layer (e.g. PZT, Lead zirconate titanate, aluminumnitride), which changes its dimension in response to electric signalsapplied by an actuation controller, a semi conductive layer, and a baselayer. In one embodiment, the physical properties of actuator 302 maydetermine the mechanical stresses that actuator 302 experiences whenelectrical current passes through it. When the piezoelectric material isactivated it exerts force on actuator 302 and causes it to bend. In oneembodiment, the resistivity of one or more actuators 302 may be measuredin an active state (Ractive) when mirror 300 is deflected at a certainangular position and compared to the resistivity at a resting state(Rrest). Feedback including Ractive may provide information to determinethe actual mirror deflection angle compared to an expected angle, and,if needed, mirror 300 deflection may be corrected. The differencebetween Rrest and Ractive may be correlated by a mirror drive into anangular deflection value that may serve to close the loop. Thisembodiment may be used for dynamic tracking of the actual mirrorposition and may optimize response, amplitude, deflection efficiency,and frequency for both linear mode and resonant mode MEMS mirrorschemes. This embodiment is described in greater detail below withreference to FIGS. 32-34.

During scanning, current (represented in the figure as the dashed line)may flow from contact 304A to contact 304B (through actuator 302A,spring 306A, mirror 300, spring 306B, and actuator 302B). Isolation gapsin semiconducting frame 308 such as isolation gap 310 may cause actuator302A and 302B to be two separate islands connected electrically throughsprings 306 and frame 308. The current flow, or any associatedelectrical parameter (voltage, current frequency, capacitance, relativedielectric constant, etc.), may be monitored by an associated positionfeedback. In case of a mechanical failure—where one of the components isdamaged—the current flow through the structure would alter and changefrom its functional calibrated values. At an extreme situation (forexample, when a spring is broken), the current would stop completely dueto a circuit break in the electrical chain by means of a faulty element.

FIG. 3B illustrates another example scanning unit 104 with a dual axisround MEMS mirror 300. In this example MEMS mirror 300 functions as atleast one deflector 114. In one embodiment, MEMS mirror 300 may have adiameter of between about 1 mm to about 5 mm. As shown, scanning unit104 may include four actuators 302 (302A, 302B, 302C, and 302D) each maybe at a differing length. In the illustrated example, the current(represented in the figure as the dashed line) flows from contact 304Ato contact 304D, but in other cases current may flow from contact 304Ato contact 304B, from contact 304A to contact 304C, from contact 304B tocontact 304C, from contact 304B to contact 304D, or from contact 304C tocontact 304D. Consistent with some embodiments, a dual axis MEMS mirrormay be configured to deflect light in a horizontal direction and in avertical direction. For example, the angles of deflection of a dual axisMEMS mirror may be between about 0° to 30° in the vertical direction andbetween about 0° to 50° in the horizontal direction. One skilled in theart will appreciate that the depicted configuration of mirror 300 mayhave numerous variations and modifications. In one example, at least ofdeflector 114 may have a dual axis square-shaped mirror or single axisround-shaped mirror. Examples of round and square mirror are depicted inFIGS. 3A and 3B as examples only. Any shape may be employed depending onsystem specifications. In one embodiment, actuators 302 may beincorporated as an integral part of at least of deflector 114, such thatpower to move MEMS mirror 300 is applied directly towards it. Inaddition, MEMS mirror 300 maybe connected to frame 308 by one or morerigid supporting elements. In another embodiment, at least of deflector114 may include an electrostatic or electromagnetic MEMS mirror.

As described above, a monostatic scanning LIDAR system utilizes at leasta portion of the same optical path for emitting projected light 204 andfor receiving reflected light 206. The light beam in the outbound pathmay be collimated and focused into a narrow beam while the reflectionsin the return path spread into a larger patch of light, due todispersion. In one embodiment, scanning unit 104 may have a largereflection area in the return path and asymmetrical deflector 216 thatredirects the reflections (i.e., reflected light 206) to sensor 116. Inone embodiment, scanning unit 104 may include a MEMS mirror with a largereflection area and negligible impact on the field of view and the framerate performance. Additional details about the asymmetrical deflector216 are provided below with reference to FIG. 2D.

In some embodiments (e.g. as exemplified in FIG. 3C), scanning unit 104may include a deflector array (e.g. a reflector array) with small lightdeflectors (e.g. mirrors). In one embodiment, implementing lightdeflector 114 as a group of smaller individual light deflectors workingin synchronization may allow light deflector 114 to perform at a highscan rate with larger angles of deflection. The deflector array mayessentially act as a large light deflector (e.g. a large mirror) interms of effective area. The deflector array may be operated using ashared steering assembly configuration that allows sensor 116 to collectreflected photons from substantially the same portion of field of view120 being concurrently illuminated by light source 112. The term“concurrently” means that the two selected functions occur duringcoincident or overlapping time periods, either where one begins and endsduring the duration of the other, or where a later one starts before thecompletion of the other.

FIG. 3C illustrates an example of scanning unit 104 with a reflectorarray 312 having small mirrors. In this embodiment, reflector array 312functions as at least one deflector 114. Reflector array 312 may includea plurality of reflector units 314 configured to pivot (individually ortogether) and steer light pulses toward field of view 120. For example,reflector array 312 may be a part of an outbound path of light projectedfrom light source 112. Specifically, reflector array 312 may directprojected light 204 towards a portion of field of view 120. Reflectorarray 312 may also be part of a return path for light reflected from asurface of an object located within an illumined portion of field ofview 120. Specifically, reflector array 312 may direct reflected light206 towards sensor 116 or towards asymmetrical deflector 216. In oneexample, the area of reflector array 312 may be between about 75 toabout 150 mm², where each reflector units 314 may have a width of about10 μm and the supporting structure may be lower than 100 μm.

According to some embodiments, reflector array 312 may include one ormore sub-groups of steerable deflectors. Each sub-group of electricallysteerable deflectors may include one or more deflector units, such asreflector unit 314. For example, each steerable deflector unit 314 mayinclude at least one of a MEMS mirror, a reflective surface assembly,and an electromechanical actuator. In one embodiment, each reflectorunit 314 may be individually controlled by an individual processor (notshown), such that it may tilt towards a specific angle along each of oneor two separate axes. Alternatively, reflector array 312 may beassociated with a common controller (e.g., processor 118) configured tosynchronously manage the movement of reflector units 314 such that atleast part of them will pivot concurrently and point in approximatelythe same direction.

In addition, at least one processor 118 may select at least onereflector unit 314 for the outbound path (referred to hereinafter as “TXMirror”) and a group of reflector units 314 for the return path(referred to hereinafter as “RX Mirror”). Consistent with the presentdisclosure, increasing the number of TX Mirrors may increase a reflectedphotons beam spread. Additionally, decreasing the number of RX Mirrorsmay narrow the reception field and compensate for ambient lightconditions (such as clouds, rain, fog, extreme heat, and otherenvironmental conditions) and improve the signal to noise ratio. Also,as indicated above, the emitted light beam is typically narrower thanthe patch of reflected light, and therefore can be fully deflected by asmall portion of the deflection array. Moreover, it is possible to blocklight reflected from the portion of the deflection array used fortransmission (e.g. the TX mirror) from reaching sensor 116, therebyreducing an effect of internal reflections of the LIDAR system 100 onsystem operation. In addition, at least one processor 118 may pivot oneor more reflector units 314 to overcome mechanical impairments anddrifts due, for example, to thermal and gain effects. In an example, oneor more reflector units 314 may move differently than intended(frequency, rate, speed etc.) and their movement may be compensated forby electrically controlling the deflectors appropriately.

FIG. 3D illustrates an exemplary LIDAR system 100 that mechanicallyscans the environment of LIDAR system 100. In this example, LIDAR system100 may include a motor or other mechanisms for rotating housing 200about the axis of the LIDAR system 100. Alternatively, the motor (orother mechanism) may mechanically rotate a rigid structure of LIDARsystem 100 on which one or more light sources 112 and one or moresensors 116 are installed, thereby scanning the environment. Asdescribed above, projecting unit 102 may include at least one lightsource 112 configured to project light emission. The projected lightemission may travel along an outbound path towards field of view 120.Specifically, the projected light emission may be reflected by deflector114A through an exit aperture 314 when projected light 204 traveltowards optional optical window 124. The reflected light emission maytravel along a return path from object 208 towards sensing unit 106. Forexample, the reflected light 206 may be reflected by deflector 114B whenreflected light 206 travels towards sensing unit 106. A person skilledin the art would appreciate that a LIDAR system with a rotationmechanism for synchronically rotating one or more light sources or oneor more sensors, may use this synchronized rotation instead of (or inaddition to) steering an internal light deflector.

In embodiments in which the scanning of field of view 120 is mechanical,the projected light emission may be directed to exit aperture 314 thatis part of a wall 316 separating projecting unit 102 from other parts ofLIDAR system 100. In some examples, wall 316 can be formed from atransparent material (e.g., glass) coated with a reflective material toform deflector 114B. In this example, exit aperture 314 may correspondto the portion of wall 316 that is not coated by the reflectivematerial. Additionally or alternatively, exit aperture 314 may include ahole or cut-away in the wall 316. Reflected light 206 may be reflectedby deflector 114B and directed towards an entrance aperture 318 ofsensing unit 106. In some examples, an entrance aperture 318 may includea filtering window configured to allow wavelengths in a certainwavelength range to enter sensing unit 106 and attenuate otherwavelengths. The reflections of object 208 from field of view 120 may bereflected by deflector 114B and hit sensor 116. By comparing severalproperties of reflected light 206 with projected light 204, at least oneaspect of object 208 may be determined. For example, by comparing a timewhen projected light 204 was emitted by light source 112 and a time whensensor 116 received reflected light 206, a distance between object 208and LIDAR system 100 may be determined. In some examples, other aspectsof object 208, such as shape, color, material, etc. may also bedetermined.

In some examples, the LIDAR system 100 (or part thereof, including atleast one light source 112 and at least one sensor 116) may be rotatedabout at least one axis to determine a three-dimensional map of thesurroundings of the LIDAR system 100. For example, the LIDAR system 100may be rotated about a substantially vertical axis as illustrated byarrow 320 in order to scan field of 120. Although FIG. 3D illustratesthat the LIDAR system 100 is rotated clock-wise about the axis asillustrated by the arrow 320, additionally or alternatively, the LIDARsystem 100 may be rotated in a counter clockwise direction. In someexamples, the LIDAR system 100 may be rotated 360 degrees about thevertical axis. In other examples, the LIDAR system 100 may be rotatedback and forth along a sector smaller than 360-degree of the LIDARsystem 100. For example, the LIDAR system 100 may be mounted on aplatform that wobbles back and forth about the axis without making acomplete rotation.

The Sensing Unit

FIGS. 4A-4E depict various configurations of sensing unit 106 and itsrole in LIDAR system 100. Specifically, FIG. 4A is a diagramillustrating an example sensing unit 106 with a detector array, FIG. 4Bis a diagram illustrating monostatic scanning using a two-dimensionalsensor, FIG. 4C is a diagram illustrating an example of atwo-dimensional sensor 116, FIG. 4D is a diagram illustrating a lensarray associated with sensor 116, and FIG. 4E includes three diagramillustrating the lens structure. One skilled in the art will appreciatethat the depicted configurations of sensing unit 106 are exemplary onlyand may have numerous alternative variations and modificationsconsistent with the principles of this disclosure.

FIG. 4A illustrates an example of sensing unit 106 with detector array400. In this example, at least one sensor 116 includes detector array400. LIDAR system 100 is configured to detect objects (e.g., bicycle208A and cloud 208B) in field of view 120 located at different distancesfrom LIDAR system 100 (could be meters or more). Objects 208 may be asolid object (e.g. a road, a tree, a car, a person), fluid object (e.g.fog, water, atmosphere particles), or object of another type (e.g. dustor a powdery illuminated object). When the photons emitted from lightsource 112 hit object 208 they either reflect, refract, or get absorbed.Typically, as shown in the figure, only a portion of the photonsreflected from object 208A enters optional optical window 124. As each˜15 cm change in distance results in a travel time difference of 1 ns(since the photons travel at the speed of light to and from object 208),the time differences between the travel times of different photonshitting the different objects may be detectable by a time-of-flightsensor with sufficiently quick response.

Sensor 116 includes a plurality of detection elements 402 for detectingphotons of a photonic pulse reflected back from field of view 120. Thedetection elements may all be included in detector array 400, which mayhave a rectangular arrangement (e.g. as shown) or any other arrangement.Detection elements 402 may operate concurrently or partiallyconcurrently with each other. Specifically, each detection element 402may issue detection information for every sampling duration (e.g. every1 nanosecond). In one example, detector array 400 may be a SiPM (Siliconphotomultipliers) which is a solid-state single-photon-sensitive devicebuilt from an array of single photon avalanche diode (, SPAD, serving asdetection elements 402) on a common silicon substrate. Similarphotomultipliers from other, non-silicon materials may also be used.Although a SiPM device works in digital/switching mode, the SiPM is ananalog device because all the microcells are read in parallel, making itpossible to generate signals within a dynamic range from a single photonto hundreds and thousands of photons detected by the different SPADs. Asmentioned above, more than one type of sensor may be implemented (e.g.SiPM and APD). Possibly, sensing unit 106 may include at least one APDintegrated into an SiPM array and/or at least one APD detector locatednext to a SiPM on a separate or common silicon substrate.

In one embodiment, detection elements 402 may be grouped into aplurality of regions 404. The regions are geometrical locations orenvironments within sensor 116 (e.g. within detector array 400)—and maybe shaped in different shapes (e.g. rectangular as shown, squares,rings, and so on, or in any other shape). While not all of theindividual detectors, which are included within the geometrical area ofa region 404, necessarily belong to that region, in most cases they willnot belong to other regions 404 covering other areas of the sensor310—unless some overlap is desired in the seams between regions. Asillustrated in FIG. 4A, the regions may be non-overlapping regions 404,but alternatively, they may overlap. Every region may be associated witha regional output circuitry 406 associated with that region. Theregional output circuitry 406 may provide a region output signal of acorresponding group of detection elements 402. For example, the regionof output circuitry 406 may be a summing circuit, but other forms ofcombined output of the individual detector into a unitary output(whether scalar, vector, or any other format) may be employed.Optionally, each region 404 is a single SiPM, but this is notnecessarily so, and a region may be a sub-portion of a single SiPM, agroup of several SiPMs, or even a combination of different types ofdetectors.

In the illustrated example, processing unit 108 is located at aseparated housing 200B (within or outside) host 210 (e.g. within vehicle110), and sensing unit 106 may include a dedicated processor 408 foranalyzing the reflected light. Alternatively, processing unit 108 may beused for analyzing reflected light 206. It is noted that LIDAR system100 may be implemented multiple housings in other ways than theillustrated example. For example, light deflector 114 may be located ina different housing than projecting unit 102 and/or sensing module 106.In one embodiment, LIDAR system 100 may include multiple housingsconnected to each other in different ways, such as: electric wireconnection, wireless connection (e.g., RF connection), fiber opticscable, and any combination of the above.

In one embodiment, analyzing reflected light 206 may include determininga time of flight for reflected light 206, based on outputs of individualdetectors of different regions. Optionally, processor 408 may beconfigured to determine the time of flight for reflected light 206 basedon the plurality of regions of output signals. In addition to the timeof flight, processing unit 108 may analyze reflected light 206 todetermine the average power across an entire return pulse, and thephoton distribution/signal may be determined over the return pulseperiod (“pulse shape”). In the illustrated example, the outputs of anydetection elements 402 may not be transmitted directly to processor 408,but rather combined (e.g. summed) with signals of other detectors of theregion 404 before being passed to processor 408. However, this is onlyan example and the circuitry of sensor 116 may transmit information froma detection element 402 to processor 408 via other routes (not via aregion output circuitry 406).

FIG. 4B is a diagram illustrating LIDAR system 100 configured to scanthe environment of LIDAR system 100 using a two-dimensional sensor 116.In the example of FIG. 4B, sensor 116 is a matrix of 4×6 detectors 410(also referred to as “pixels”). In one embodiment, a pixel size may beabout 1×1 mm. Sensor 116 is two-dimensional in the sense that it hasmore than one set (e.g. row, column) of detectors 410 in twonon-parallel axes (e.g. orthogonal axes, as exemplified in theillustrated examples). The number of detectors 410 in sensor 116 mayvary between differing implementations, e.g. depending on the desiredresolution, signal to noise ratio (SNR), desired detection distance, andso on. For example, sensor 116 may have anywhere between 5 and 5.000pixels. In another example (not shown in the figure) Also, sensor 116may be a one-dimensional matrix (e.g. 1×8 pixels).

It is noted that each detector 410 may include a plurality of detectionelements 402, such as Avalanche Photo Diodes (APD), Single PhotonAvalanche Diodes (SPADs), combination of Avalanche Photo Diodes (APD)and Single Photon Avalanche Diodes (SPADs) or detecting elements thatmeasure both the time of flight from a laser pulse transmission event tothe reception event and the intensity of the received photons. Forexample, each detector 410 may include anywhere between 20 and 5,000SPADs. The outputs of detection elements 402 in each detector 410 may besummed, averaged, or otherwise combined to provide a unified pixeloutput.

In the illustrated example, sensing unit 106 may include atwo-dimensional sensor 116 (or a plurality of two-dimensional sensors116), whose field of view is smaller than field of view 120 of LIDARsystem 100. In this discussion, field of view 120 (the overall field ofview which can be scanned by LIDAR system 100 without moving, rotatingor rolling in any direction) is denoted “first FOV 412”, and the smallerFOV of sensor 116 is denoted “second FOV 412” (interchangeably“instantaneous FOV”). The coverage area of second FOV 414 relative tothe first FOV 412 may differ, depending on the specific use of LIDARsystem 100, and may be, for example, between 0.5% and 50%. In oneexample, second FOV 412 may be between about 0.05° and 1° elongated inthe vertical dimension. Even if LIDAR system 100 includes more than onetwo-dimensional sensor 116, the combined field of view of the sensorsarray may still be smaller than the first FOV 412, e.g. by a factor ofat least 5, by a factor of at least 10, by a factor of at least 20, orby a factor of at least 50, for example.

In order to cover first FOV 412, scanning unit 106 may direct photonsarriving from different parts of the environment to sensor 116 atdifferent times. In the illustrated monostatic configuration, togetherwith directing projected light 204 towards field of view 120 and whenleast one light deflector 114 is located in an instantaneous position,scanning unit 106 may also direct reflected light 206 to sensor 116.Typically, at every moment during the scanning of first FOV 412, thelight beam emitted by LIDAR system 100 covers part of the environmentwhich is larger than the second FOV 414 (in angular opening) andincludes the part of the environment from which light is collected byscanning unit 104 and sensor 116.

FIG. 4C is a diagram illustrating an example of a two-dimensional sensor116. In this embodiment, sensor 116 is a matrix of 8×5 detectors 410 andeach detector 410 includes a plurality of detection elements 402. In oneexample, detector 410A is located in the second row (denoted “R2”) andthird column (denoted “C3”) of sensor 116, which includes a matrix of4×3 detection elements 402. In another example, detector 410B located inthe fourth row (denoted “R4”) and sixth column (denoted “C6”) of sensor116 includes a matrix of 3×3 detection elements 402. Accordingly, thenumber of detection elements 402 in each detector 410 may be constant,or may vary, and differing detectors 410 in a common array may have adifferent number of detection elements 402. The outputs of all detectionelements 402 in each detector 410 may be summed, averaged, or otherwisecombined to provide a single pixel-output value. It is noted that whiledetectors 410 in the example of FIG. 4C are arranged in a rectangularmatrix (straight rows and straight columns), other arrangements may alsobe used, e.g. a circular arrangement or a honeycomb arrangement.

According to some embodiments, measurements from each detector 410 mayenable determination of the time of flight from a light pulse emissionevent to the reception event and the intensity of the received photons.The reception event may be the result of the light pulse being reflectedfrom object 208. The time of flight may be a timestamp value thatrepresents the distance of the reflecting object to optional opticalwindow 124. Time of flight values may be realized by photon detectionand counting methods, such as Time Correlated Single Photon Counters(TCSPC), analog methods for photon detection such as signal integrationand qualification (via analog to digital converters or plaincomparators) or otherwise.

In some embodiments and with reference to FIG. 4B, during a scanningcycle, each instantaneous position of at least one light deflector 114may be associated with a particular portion 122 of field of view 120.The design of sensor 116 enables an association between the reflectedlight from a single portion of field of view 120 and multiple detectors410. Therefore, the scanning resolution of LIDAR system may berepresented by the number of instantaneous positions (per scanningcycle) times the number of detectors 410 in sensor 116. The informationfrom each detector 410 (i.e., each pixel) represents the basic dataelement that from which the captured field of view in thethree-dimensional space is built. This may include, for example, thebasic element of a point cloud representation, with a spatial positionand an associated reflected intensity value. In one embodiment, thereflections from a single portion of field of view 120 that are detectedby multiple detectors 410 may be returning from different objectslocated in the single portion of field of view 120. For example, thesingle portion of field of view 120 may be greater than 50×50 cm at thefar field, which can easily include two, three, or more objects partlycovered by each other.

FIG. 4D is a cross cut diagram of a part of sensor 116, in accordancewith examples of the presently disclosed subject matter. The illustratedpart of sensor 116 includes a part of a detector array 400 whichincludes four detection elements 402 (e.g., four SPADs, four APDs).Detector array 400 may be a photodetector sensor realized incomplementary metal-oxide-semiconductor (CMOS). Each of the detectionelements 402 has a sensitive area, which is positioned within asubstrate surrounding. While not necessarily so, sensor 116 may be usedin a monostatic LiDAR system having a narrow field of view (e.g.,because scanning unit 104 scans different parts of the field of view atdifferent times). The narrow field of view for the incoming lightbeam—if implemented—eliminates the problem of out-of-focus imaging. Asexemplified in FIG. 4D, sensor 116 may include a plurality of lenses 422(e.g., microlenses), each lens 422 may direct incident light toward adifferent detection element 402 (e.g., toward an active area ofdetection element 402), which may be usable when out-of-focus imaging isnot an issue. Lenses 422 may be used for increasing an optical fillfactor and sensitivity of detector array 400, because most of the lightthat reaches sensor 116 may be deflected toward the active areas ofdetection elements 402

Detector array 400, as exemplified in FIG. 4D, may include severallayers built into the silicon substrate by various methods (e.g.,implant) resulting in a sensitive area, contact elements to the metallayers and isolation elements (e.g., shallow trench implant STI, guardrings, optical trenches, etc.). The sensitive area may be a volumetricelement in the CMOS detector that enables the optical conversion ofincoming photons into a current flow given an adequate voltage bias isapplied to the device. In the case of a APD/SPAD, the sensitive areawould be a combination of an electrical field that pulls electronscreated by photon absorption towards a multiplication area where aphoton induced electron is amplified creating a breakdown avalanche ofmultiplied electrons.

A front side illuminated detector (e.g., as illustrated in FIG. 4D) hasthe input optical port at the same side as the metal layers residing ontop of the semiconductor (Silicon). The metal layers are required torealize the electrical connections of each individual photodetectorelement (e.g., anode and cathode) with various elements such as: biasvoltage, quenching/ballast elements, and other photodetectors in acommon array. The optical port through which the photons impinge uponthe detector sensitive area is comprised of a passage through the metallayer. It is noted that passage of light from some directions throughthis passage may be blocked by one or more metal layers (e.g., metallayer ML6, as illustrated for the leftmost detector elements 402 in FIG.4D). Such blockage reduces the total optical light absorbing efficiencyof the detector.

FIG. 4E illustrates three detection elements 402, each with anassociated lens 422, in accordance with examples of the presentingdisclosed subject matter. Each of the three detection elements of FIG.4E, denoted 402(1), 402(2), and 402(3), illustrates a lens configurationwhich may be implemented in associated with one or more of the detectingelements 402 of sensor 116. It is noted that combinations of these lensconfigurations may also be implemented.

In the lens configuration illustrated with regards to detection element402(1), a focal point of the associated lens 422 may be located abovethe semiconductor surface. Optionally, openings in different metallayers of the detection element may have different sizes aligned withthe cone of focusing light generated by the associated lens 422. Such astructure may improve the signal-to-noise and resolution of the array400 as a whole device. Large metal layers may be important for deliveryof power and ground shielding. This approach may be useful, e.g., with amonostatic LiDAR design with a narrow field of view where the incominglight beam is comprised of parallel rays and the imaging focus does nothave any consequence to the detected signal.

In the lens configuration illustrated with regards to detection element402(2), an efficiency of photon detection by the detection elements 402may be improved by identifying a sweet spot. Specifically, aphotodetector implemented in CMOS may have a sweet spot in the sensitivevolume area where the probability of a photon creating an avalancheeffect is the highest. Therefore, a focal point of lens 422 may bepositioned inside the sensitive volume area at the sweet spot location,as demonstrated by detection elements 402(2). The lens shape anddistance from the focal point may take into account the refractiveindices of all the elements the laser beam is passing along the way fromthe lens to the sensitive sweet spot location buried in thesemiconductor material.

In the lens configuration illustrated with regards to the detectionelement on the right of FIG. 4E, an efficiency of photon absorption inthe semiconductor material may be improved using a diffuser andreflective elements. Specifically, a near IR wavelength requires asignificantly long path of silicon material in order to achieve a highprobability of absorbing a photon that travels through. In a typicallens configuration, a photon may traverse the sensitive area and may notbe absorbed into a detectable electron. A long absorption path thatimproves the probability for a photon to create an electron renders thesize of the sensitive area towards less practical dimensions (tens ofurn for example) for a CMOS device fabricated with typical foundryprocesses. The rightmost detector element in FIG. 4E demonstrates atechnique for processing incoming photons. The associated lens 422focuses the incoming light onto a diffuser element 424. In oneembodiment, light sensor 116 may further include a diffuser located inthe gap distant from the outer surface of at least some of thedetectors. For example, diffuser 424 may steer the light beam sideways(e.g., as perpendicular as possible) towards the sensitive area and thereflective optical trenches 426. The diffuser is located at the focalpoint, above the focal point, or below the focal point. In thisembodiment, the incoming light may be focused on a specific locationwhere a diffuser element is located. Optionally, detector element 422 isdesigned to optically avoid the inactive areas where a photon inducedelectron may get lost and reduce the effective detection efficiency.Reflective optical trenches 426 (or other forms of optically reflectivestructures) cause the photons to bounce back and forth across thesensitive area, thus increasing the likelihood of detection. Ideally,the photons will get trapped in a cavity consisting of the sensitivearea and the reflective trenches indefinitely until the photon isabsorbed and creates an electron/hole pair.

Consistent with the present disclosure, a long path is created for theimpinging photons to be absorbed and contribute to a higher probabilityof detection. Optical trenches may also be implemented in detectingelement 422 for reducing cross talk effects of parasitic photons createdduring an avalanche that may leak to other detectors and cause falsedetection events. According to some embodiments, a photo detector arraymay be optimized so that a higher yield of the received signal isutilized, meaning, that as much of the received signal is received andless of the signal is lost to internal degradation of the signal. Thephoto detector array may be improved by: (a) moving the focal point at alocation above the semiconductor surface, optionally by designing themetal layers above the substrate appropriately; (b) by steering thefocal point to the most responsive/sensitive area (or “sweet spot”) ofthe substrate and (c) adding a diffuser above the substrate to steer thesignal toward the “sweet spot” and/or adding reflective material to thetrenches so that deflected signals are reflected back to the “sweetspot.”

While in some lens configurations, lens 422 may be positioned so thatits focal point is above a center of the corresponding detection element402, it is noted that this is not necessarily so. In other lensconfiguration, a position of the focal point of the lens 422 withrespect to a center of the corresponding detection element 402 isshifted based on a distance of the respective detection element 402 froma center of the detection array 400. This may be useful in relativelylarger detection arrays 400, in which detector elements further from thecenter receive light in angles which are increasingly off-axis. Shiftingthe location of the focal points (e.g., toward the center of detectionarray 400) allows correcting for the incidence angles. Specifically,shifting the location of the focal points (e.g., toward the center ofdetection array 400) allows correcting for the incidence angles whileusing substantially identical lenses 422 for all detection elements,which are positioned at the same angle with respect to a surface of thedetector.

Adding an array of lenses 422 to an array of detection elements 402 maybe useful when using a relatively small sensor 116 which covers only asmall part of the field of view because in such a case, the reflectionsignals from the scene reach the detectors array 400 from substantiallythe same angle, and it is, therefore, easy to focus all the light ontoindividual detectors. It is also noted, that in one embodiment, lenses422 may be used in LIDAR system 100 for favoring about increasing theoverall probability of detection of the entire array 400 (preventingphotons from being “wasted” in the dead area betweendetectors/sub-detectors) at the expense of spatial distinctiveness. Thisembodiment is in contrast to prior art implementations such as CMOS RGBcamera, which prioritize spatial distinctiveness (i.e., light thatpropagates in the direction of detection element A is not allowed to bedirected by the lens toward detection element B, that is, to “bleed” toanother detection element of the array). Optionally, sensor 116 includesan array of lens 422, each being correlated to a corresponding detectionelement 402, while at least one of the lenses 422 deflects light whichpropagates to a first detection element 402 toward a second detectionelement 402 (thereby it may increase the overall probability ofdetection of the entire array).

Specifically, consistent with some embodiments of the presentdisclosure, light sensor 116 may include an array of light detectors(e.g., detector array 400), each light detector (e.g., detector 410)being configured to cause an electric current to flow when light passesthrough an outer surface of a respective detector. In addition, lightsensor 116 may include at least one micro-lens configured to directlight toward the array of light detectors, the at least one micro-lenshaving a focal point. Light sensor 116 may further include at least onelayer of conductive material interposed between the at least onemicro-lens and the array of light detectors and having a gap therein topermit light to pass from the at least one micro-lens to the array, theat least one layer being sized to maintain a space between the at leastone micro-lens and the array to cause the focal point (e.g., the focalpoint may be a plane) to be located in the gap, at a location spacedfrom the detecting surfaces of the array of light detectors.

In related embodiments, each detector may include a plurality of SinglePhoton Avalanche Diodes (SPADs) or a plurality of Avalanche Photo Diodes(APD). The conductive material may be a multi-layer metal constriction,and the at least one layer of conductive material may be electricallyconnected to detectors in the array. In one example, the at least onelayer of conductive material includes a plurality of layers. Inaddition, the gap may be shaped to converge from the at least onemicro-lens toward the focal point, and to diverge from a region of thefocal point toward the array. In other embodiments, light sensor 116 mayfurther include at least one reflector adjacent each photo detector. Inone embodiment, a plurality of micro-lenses may be arranged in a lensarray and the plurality of detectors may be arranged in a detectorarray. In another embodiment, the plurality of micro-lenses may includea single lens configured to project light to a plurality of detectors inthe array.

The Processing Unit

FIGS. 5A-5C depict different functionalities of processing units 108 inaccordance with some embodiments of the present disclosure.Specifically, FIG. 5A is a diagram illustrating emission patterns in asingle frame-time for a single portion of the field of view, FIG. 5B isa diagram illustrating emission scheme in a single frame-time for thewhole field of view, and, FIG. 5C is a diagram illustrating the actuallight emission projected towards field of view during a single scanningcycle.

FIG. 5A illustrates four examples of emission patterns in a singleframe-time for a single portion 122 of field of view 120 associated withan instantaneous position of at least one light deflector 114.Consistent with embodiments of the present disclosure, processing unit108 may control at least one light source 112 and light deflector 114(or coordinate the operation of at least one light source 112 and atleast one light deflector 114) in a manner enabling light flux to varyover a scan of field of view 120. Consistent with other embodiments,processing unit 108 may control only at least one light source 112 andlight deflector 114 may be moved or pivoted in a fixed predefinedpattern.

Diagrams A-D in FIG. 5A depict the power of light emitted towards asingle portion 122 of field of view 120 over time. In Diagram A,processor 118 may control the operation of light source 112 in a mannersuch that during scanning of field of view 120 an initial light emissionis projected toward portion 122 of field of view 120. When projectingunit 102 includes a pulsed-light light source, the initial lightemission may include one or more initial pulses (also referred to as“pilot pulses”). Processing unit 108 may receive from sensor 116 pilotinformation about reflections associated with the initial lightemission. In one embodiment, the pilot information may be represented asa single signal based on the outputs of one or more detectors (e.g. oneor more SPADs, one or more APDs, one or more SiPMs, etc.) or as aplurality of signals based on the outputs of multiple detectors. In oneexample, the pilot information may include analog and/or digitalinformation. In another example, the pilot information may include asingle value and/or a plurality of values (e.g. for different timesand/or parts of the segment).

Based on information about reflections associated with the initial lightemission, processing unit 108 may be configured to determine the type ofsubsequent light emission to be projected towards portion 122 of fieldof view 120. The determined subsequent light emission for the particularportion of field of view 120 may be made during the same scanning cycle(i.e., in the same frame) or in a subsequent scanning cycle (i.e., in asubsequent frame). This embodiment is described in greater detail belowwith reference to FIGS. 23-25.

In Diagram B, processor 118 may control the operation of light source112 in a manner such that during scanning of field of view 120 lightpulses in different intensities are projected towards a single portion122 of field of view 120. In one embodiment, LIDAR system 100 may beoperable to generate depth maps of one or more different types, such asany one or more of the following types: point cloud model, polygon mesh,depth image (holding depth information for each pixel of an image or ofa 2D array), or any other type of 3D model of a scene. The sequence ofdepth maps may be a temporal sequence, in which different depth maps aregenerated at a different time. Each depth map of the sequence associatedwith a scanning cycle (interchangeably “frame”) may be generated withinthe duration of a corresponding subsequent frame-time. In one example, atypical frame-time may last less than a second. In some embodiments,LIDAR system 100 may have a fixed frame rate (e.g. 10 frames per second,25 frames per second, 50 frames per second) or the frame rate may bedynamic. In other embodiments, the frame-times of different frames maynot be identical across the sequence. For example, LIDAR system 100 mayimplement a 10 frames-per-second rate that includes generating a firstdepth map in 100 milliseconds (the average), a second frame in 92milliseconds, a third frame at 142 milliseconds, and so on.

In Diagram C, processor 118 may control the operation of light source112 in a manner such that during scanning of field of view 120 lightpulses associated with different durations are projected towards asingle portion 122 of field of view 120. In one embodiment, LIDAR system100 may be operable to generate a different number of pulses in eachframe. The number of pulses may vary between 0 to 32 pulses (e.g., 1, 5,12, 28, or more pulses) and may be based on information derived fromprevious emissions. The time between light pulses may depend on desireddetection range and can be between 500 ns and 5000 ns. In one example,processing unit 108 may receive from sensor 116 information aboutreflections associated with each light-pulse. Based on the information(or the lack of information), processing unit 108 may determine ifadditional light pulses are needed. It is noted that the durations ofthe processing times and the emission times in diagrams A-D are notin-scale. Specifically, the processing time may be substantially longerthan the emission time. In diagram D, projecting unit 102 may include acontinuous-wave light source. In one embodiment, the initial lightemission may include a period of time where light is emitted and thesubsequent emission may be a continuation of the initial emission, orthere may be a discontinuity. In one embodiment, the intensity of thecontinuous emission may change over time.

Consistent with some embodiments of the present disclosure, the emissionpattern may be determined per each portion of field of view 120. Inother words, processor 118 may control the emission of light to allowdifferentiation in the illumination of different portions of field ofview 120. In one example, processor 118 may determine the emissionpattern for a single portion 122 of field of view 120, based ondetection of reflected light from the same scanning cycle (e.g., theinitial emission), which makes LIDAR system 100 extremely dynamic. Inanother example, processor 118 may determine the emission pattern for asingle portion 122 of field of view 120, based on detection of reflectedlight from a previous scanning cycle. The differences in the patterns ofthe subsequent emissions may result from determining different valuesfor light-source parameters for the subsequent emission, such as any oneof the following.

-   -   a. Overall energy of the subsequent emission.    -   b. Energy profile of the subsequent emission.    -   c. A number of light-pulse-repetition per frame.    -   d. Light modulation characteristics such as duration, rate,        peak, average power, and pulse shape.    -   e. Wave properties of the subsequent emission, such as        polarization, wavelength, etc.

Consistent with the present disclosure, the differentiation in thesubsequent emissions may be put to different uses. In one example, it ispossible to limit emitted power levels in one portion of field of view120 where safety is a consideration, while emitting higher power levels(thus improving signal-to-noise ratio and detection range) for otherportions of field of view 120. This is relevant for eye safety, but mayalso be relevant for skin safety, safety of optical systems, safety ofsensitive materials, and more. In another example, it is possible todirect more energy towards portions of field of view 120 where it willbe of greater use (e.g. regions of interest, further distanced targets,low reflection targets, etc.) while limiting the lighting energy toother portions of field of view 120 based on detection results from thesame frame or previous frame. It is noted that processing unit 108 mayprocess detected signals from a single instantaneous field of viewseveral times within a single scanning frame time; for example,subsequent emission may be determined upon after every pulse emitted, orafter a number of pulses emitted.

FIG. 5B illustrates three examples of emission schemes in a singleframe-time for field of view 120. Consistent with embodiments of thepresent disclosure, at least on processing unit 108 may use obtainedinformation to dynamically adjust the operational mode of LIDAR system100 and/or determine values of parameters of specific components ofLIDAR system 100. The obtained information may be determined fromprocessing data captured in field of view 120, or received (directly orindirectly) from host 210. Processing unit 108 may use the obtainedinformation to determine a scanning scheme for scanning the differentportions of field of view 120. The obtained information may include acurrent light condition, a current weather condition, a current drivingenvironment of the host vehicle, a current location of the host vehicle,a current trajectory of the host vehicle, a current topography of roadsurrounding the host vehicle, or any other condition or objectdetectable through light reflection. In some embodiments, the determinedscanning scheme may include at least one of the following: (a) adesignation of portions within field of view 120 to be actively scannedas part of a scanning cycle, (b) a projecting plan for projecting unit102 that defines the light emission profile at different portions offield of view 120; (c) a deflecting plan for scanning unit 104 thatdefines, for example, a deflection direction, frequency, and designatingidle elements within a reflector array; and (d) a detection plan forsensing unit 106 that defines the detectors sensitivity or responsivitypattern.

In addition, processing unit 108 may determine the scanning scheme atleast partially by obtaining an identification of at least one region ofinterest within the field of view 120 and at least one region ofnon-interest within the field of view 120. In some embodiments,processing unit 108 may determine the scanning scheme at least partiallyby obtaining an identification of at least one region of high interestwithin the field of view 120 and at least one region of lower-interestwithin the field of view 120. The identification of the at least oneregion of interest within the field of view 120 may be determined, forexample, from processing data captured in field of view 120, based ondata of another sensor (e.g. camera, GPS), received (directly orindirectly) from host 210, or any combination of the above. In someembodiments, the identification of at least one region of interest mayinclude identification of portions, areas, sections, pixels, or objectswithin field of view 120 that are important to monitor. Examples ofareas that may be identified as regions of interest may include,crosswalks, moving objects, people, nearby vehicles or any otherenvironmental condition or object that may be helpful in vehiclenavigation. Examples of areas that may be identified as regions ofnon-interest (or lower-interest) may be static (non-moving) far-awaybuildings, a skyline, an area above the horizon and objects in the fieldof view. Upon obtaining the identification of at least one region ofinterest within the field of view 120, processing unit 108 may determinethe scanning scheme or change an existing scanning scheme. Further todetermining or changing the light-source parameters (as describedabove), processing unit 108 may allocate detector resources based on theidentification of the at least one region of interest. In one example,to reduce noise, processing unit 108 may activate detectors 410 where aregion of interest is expected and disable detectors 410 where regionsof non-interest are expected. In another example, processing unit 108may change the detector sensitivity, e.g., increasing sensor sensitivityfor long range detection where the reflected power is low.

Diagrams A-C in FIG. 5B depict examples of different scanning schemesfor scanning field of view 120. Each square in field of view 120represents a different portion 122 associated with an instantaneousposition of at least one light deflector 114. Legend 500 details thelevel of light flux represented by the filling pattern of the squares.Diagram A depicts a first scanning scheme in which all of the portionshave the same importance/priority and a default light flux is allocatedto them. The first scanning scheme may be utilized in a start-up phaseor periodically interleaved with another scanning scheme to monitor thewhole field of view for unexpected/new objects. In one example, thelight source parameters in the first scanning scheme may be configuredto generate light pulses at constant amplitudes. Diagram B depicts asecond scanning scheme in which a portion of field of view 120 isallocated with high light flux while the rest of field of view 120 isallocated with default light flux and low light flux. The portions offield of view 120 that are the least interesting may be allocated withlow light flux. Diagram C depicts a third scanning scheme in which acompact vehicle and a bus (see silhouettes) are identified in field ofview 120. In this scanning scheme, the edges of the vehicle and bus maybe tracked with high power and the central mass of the vehicle and busmay be allocated with less light flux (or no light flux). Such lightflux allocation enables concentration of more of the optical budget onthe edges of the identified objects and less on their center which haveless importance.

FIG. 5C illustrating the emission of light towards field of view 120during a single scanning cycle. In the depicted example, field of view120 is represented by an 8×9 matrix, where each of the 72 cellscorresponds to a separate portion 122 associated with a differentinstantaneous position of at least one light deflector 114. In thisexemplary scanning cycle, each portion includes one or more white dotsthat represent the number of light pulses projected toward that portion,and some portions include black dots that represent reflected light fromthat portion detected by sensor 116. As shown, field of view 120 isdivided into three sectors: sector I on the right side of field of view120, sector II in the middle of field of view 120, and sector III on theleft side of field of view 120. In this exemplary scanning cycle, sectorI was initially allocated with a single light pulse per portion; sectorII, previously identified as a region of interest, was initiallyallocated with three light pulses per portion; and sector III wasinitially allocated with two light pulses per portion. Also as shown,scanning of field of view 120 reveals four objects 208: two free-formobjects in the near field (e.g., between 5 and 50 meters), arounded-square object in the mid field (e.g., between 50 and 150meters), and a triangle object in the far field (e.g., between 150 and500 meters). While the discussion of FIG. 5C uses number of pulses as anexample of light flux allocation, it is noted that light flux allocationto different parts of the field of view may also be implemented in otherways such as: pulse duration, pulse angular dispersion, wavelength,instantaneous power, photon density at different distances from lightsource 112, average power, pulse power intensity, pulse width, pulserepetition rate, pulse sequence, pulse duty cycle, wavelength, phase,polarization, and more. The illustration of the light emission as asingle scanning cycle in FIG. 5C demonstrates different capabilities ofLIDAR system 100. In a first embodiment, processor 118 is configured touse two light pulses to detect a first object (e.g., the rounded-squareobject) at a first distance, and to use three light pulses to detect asecond object (e.g., the triangle object) at a second distance greaterthan the first distance. This embodiment is described in greater detailbelow with reference to FIGS. 11-13. In a second embodiment, processor118 is configured to allocate more light to portions of the field ofview where a region of interest is identified. Specifically, in thepresent example, sector II was identified as a region of interest andaccordingly it was allocated with three light pulses while the rest offield of view 120 was allocated with two or less light pulses. Thisembodiment is described in greater detail below with reference to FIGS.20-22. In a third embodiment, processor 118 is configured to controllight source 112 in a manner such that only a single light pulse isprojected toward to portions B1, B2, and C1 in FIG. 5C, although theyare part of sector III that was initially allocated with two lightpulses per portion. This occurs because the processing unit 108 detectedan object in the near field based on the first light pulse. Thisembodiment is described in greater detail below with reference to FIGS.23-25. Allocation of less than maximal amount of pulses may also be aresult of other considerations. For examples, in at least some regions,detection of object at a first distance (e.g. a near field object) mayresult in reducing an overall amount of light emitted to this portion offield of view 120. This embodiment is described in greater detail belowwith reference to FIGS. 14-16. Other reasons to for determining powerallocation to different portions is discussed below with respect toFIGS. 29-31, FIGS. 53-55, and FIGS. 50-52.

Additional details and examples on different components of LIDAR system100 and their associated functionalities are included in Applicant'sU.S. patent application Ser. No. 15/391,916 filed Dec. 28, 2016;Applicant's U.S. patent application Ser. No. 15/393,749 filed Dec. 29,2016; Applicant's U.S. patent application Ser. No. 15/393,285 filed Dec.29, 2016; and Applicant's U.S. patent application Ser. No. 15/393,593filed Dec. 29, 2016, which are incorporated herein by reference in theirentirety.

Example Implementation: Vehicle

FIGS. 6A-6C illustrate the implementation of LIDAR system 100 in avehicle (e.g., vehicle 110). Any of the aspects of LIDAR system 100described above or below may be incorporated into vehicle 110 to providea range-sensing vehicle. Specifically, in this example, LIDAR system 100integrates multiple scanning units 104 and potentially multipleprojecting units 102 in a single vehicle. In one embodiment, a vehiclemay take advantage of such a LIDAR system to improve power, range andaccuracy in the overlap zone and beyond it, as well as redundancy insensitive parts of the FOV (e.g. the forward movement direction of thevehicle). As shown in FIG. 6A, vehicle 110 may include a first processor118A for controlling the scanning of field of view 120A, a secondprocessor 118B for controlling the scanning of field of view 120B, and athird processor 118C for controlling synchronization of scanning the twofields of view. In one example, processor 118C may be the vehiclecontroller and may have a shared interface between first processor 118Aand second processor 118B. The shared interface may enable an exchangingof data at intermediate processing levels and a synchronization ofscanning of the combined field of view in order to form an overlap inthe temporal and/or spatial space. In one embodiment, the data exchangedusing the shared interface may be: (a) time of flight of receivedsignals associated with pixels in the overlapped field of view and/or inits vicinity; (b) laser steering position status; (c) detection statusof objects in the field of view.

FIG. 6B illustrates overlap region 600 between field of view 120A andfield of view 120B. In the depicted example, the overlap region isassociated with 24 portions 122 from field of view 120A and 24 portions122 from field of view 120B. Given that the overlap region is definedand known by processors 118A and 118B, each processor may be designed tolimit the amount of light emitted in overlap region 600 in order toconform with an eye safety limit that spans multiple source lights, orfor other reasons such as maintaining an optical budget. In addition,processors 118A and 118B may avoid interferences between the lightemitted by the two light sources by loose synchronization between thescanning unit 104A and scanning unit 104B, and/or by control of thelaser transmission timing, and/or the detection circuit enabling timing.

FIG. 6C illustrates how overlap region 600 between field of view 120Aand field of view 120B may be used to increase the detection distance ofvehicle 110. Consistent with the present disclosure, two or more lightsources 112 projecting their nominal light emission into the overlapzone may be leveraged to increase the effective detection range. Theterm “detection range” may include an approximate distance from vehicle110 at which LIDAR system 100 can clearly detect an object. In oneembodiment, the maximum detection range of LIDAR system 100 is about 300meters, about 400 meters, or about 500 meters. For example, for adetection range of 200 meters, LIDAR system 100 may detect an objectlocated 200 meters (or less) from vehicle 110 at more than 95%, morethan 99%, more than 99.5% of the times. Even when the object'sreflectivity may be less than 50% (e.g., less than 20%, less than 10%,or less than 5%). In addition, LIDAR system 100 may have less than 1%false alarm rate. In one embodiment, light from projected from two lightsources that are collocated in the temporal and spatial space can beutilized to improve SNR and therefore increase the range and/or qualityof service for an object located in the overlap region. Processor 118Cmay extract high-level information from the reflected light in field ofview 120A and 120B. The term “extracting information” may include anyprocess by which information associated with objects, individuals,locations, events, etc., is identified in the captured image data by anymeans known to those of ordinary skill in the art. In addition,processors 118A and 118B may share the high-level information, such asobjects (road delimiters, background, pedestrians, vehicles, etc.), andmotion vectors, to enable each processor to become alert to theperipheral regions about to become regions of interest. For example, amoving object in field of view 120A may be determined to soon beentering field of view 120B.

Example Implementation: Surveillance System

FIG. 6D illustrates the implementation of LIDAR system 100 in asurveillance system. As mentioned above, LIDAR system 100 may be fixedto a stationary object 650 that may include a motor or other mechanismsfor rotating the housing of the LIDAR system 100 to obtain a wider fieldof view. Alternatively, the surveillance system may include a pluralityof LIDAR units. In the example depicted in FIG. 6D, the surveillancesystem may use a single rotatable LIDAR system 100 to obtain 3D datarepresenting field of view 120 and to process the 3D data to detectpeople 652, vehicles 654, changes in the environment, or any other formof security-significant data.

Consistent with some embodiment of the present disclosure, the 3D datamay be analyzed to monitor retail business processes. In one embodiment,the 3D data may be used in retail business processes involving physicalsecurity (e.g., detection of: an intrusion within a retail facility, anact of vandalism within or around a retail facility, unauthorized accessto a secure area, and suspicious behavior around cars in a parking lot).In another embodiment, the 3D data may be used in public safety (e.g.,detection of: people slipping and falling on store property, a dangerousliquid spill or obstruction on a store floor, an assault or abduction ina store parking lot, an obstruction of a fire exit, and crowding in astore area or outside of the store). In another embodiment, the 3D datamay be used for business intelligence data gathering (e.g., tracking ofpeople through store areas to determine, for example, how many people gothrough, where they dwell, how long they dwell, how their shoppinghabits compare to their purchasing habits).

Consistent with other embodiments of the present disclosure, the 3D datamay be analyzed and used for traffic enforcement. Specifically, the 3Ddata may be used to identify vehicles traveling over the legal speedlimit or some other road legal requirement. In one example, LIDAR system100 may be used to detect vehicles that cross a stop line or designatedstopping place while a red traffic light is showing. In another example,LIDAR system 100 may be used to identify vehicles traveling in lanesreserved for public transportation. In yet another example, LIDAR system100 may be used to identify vehicles turning in intersections wherespecific turns are prohibited on red.

It should be noted that while examples of various disclosed embodimentshave been described above and below with respect to a control unit thatcontrols scanning of a deflector, the various features of the disclosedembodiments are not limited to such systems. Rather, the techniques forallocating light to various portions of a LIDAR FOV may be applicable totype of light-based sensing system (LIDAR or otherwise) in which theremay be a desire or need to direct different amounts of light todifferent portions of field of view. In some cases, such lightallocation techniques may positively impact detection capabilities, asdescribed herein, but other advantages may also result.

Detector-Array Based Scanning LIDAR

Many extant LIDAR systems provide for flashing of lasers onto a scene,which then produce reflections and construct images of the scene usingthe reflections. However, such systems may provide low detail (e.g., lowresolution) and may provide no redundancy in measurement.

Systems and methods of the present disclosure may thus allow for the useof a moving (or scanning) laser spot with a plurality of detectors.Accordingly, greater detail may be obtained compared with extant systemsin addition to a multiplicity of measurements for each spot. Suchmultiplicity may provide additional detail and/or provide redundantmeasurements to use in, for example, error correction.

FIG. 7 illustrates an example method 700 for detecting objects using aLIDAR system. Method 700 may be performed by one or more processors(e.g., at least one processor 118 of processing unit 108 of LIDAR system100 as depicted in FIG. 1A and/or two processors 118 of processing unit108 of the LIDAR system 100 depicted in FIG. 2A).

At step 701, processor 118 controls light emission of a light source(e.g., light source 112 of FIG. 1A, laser diode 202 of light source 112of FIG. 2A, and/or plurality of light sources 102 of FIG. 2B). Forexample, processor 118 may power up the light source or power down thelight source. In addition, processor 118 may vary the timing of pulsesfrom the light source. Alternatively or concurrently, processor 118 mayvary the length of pulses from the light source. By way of furtherexample, processor 118 may alternatively or concurrently vary spatialdimensions (e.g., length or width or otherwise alter a cross-sectionalarea) of light pulses emitted from the light source. In a yet furtherexample, processor 118 may alternatively or concurrently vary theamplitude and/or frequency of pulses from the light source. In yetanother example, processor 118 may change parameters of a continuouswave (CW) or quasi-CW light emission (e.g., its amplitude, itsmodulation, its phase, or the like) from the light source. Although thelight source may be referred to as a “laser,” alternative light sourcesmay be used alternatively to or concurrently with lasers. For example, alight emitting diode (LED) based light source or likewise may be used asthe light source. In some embodiments, the controlling of the lightemission may include controlling the operation of other components ofthe emission path in addition to the light source itself. For example,processor 118 may further control the light source by controllingcollimation optics and/or other optical components on the transmissionpath of the LIDAR system.

At step 703, processor 118 scans a field of view (e.g., field of view120 of FIGS. 1A and 2A) by repeatedly moving at least one lightdeflector (e.g., light deflector 114 of FIG. 1A, deflector 114A and/ordeflector 114B of FIG. 2A, and/or one-way deflector 114 of FIG. 2B)located in an outbound path of the light source. In some embodiments,the at least one light deflector may include a pivotable MEMS mirror(e.g., MEMS mirror 300 of FIG. 3A).

In some embodiments, processor 118 may move the at least one lightdeflector such that, during a single scanning cycle of the field ofview, the at least one light deflector may be located in a plurality ofdifferent instantaneous positions (e.g., the deflector may be controlledsuch that the deflector moves from or through one instantaneous positionto another during the scan of the LIDAR FOV). For example, the at leastone light deflector may be moved continuously or non-continuously fromone of the plurality of positions to another (optionally with additionalpositions and/or repetitions) during the scanning cycle. As used herein,the term “move” may refer to a physical movement of the deflector or amodification of an electrical property, an optical property of thedeflector (e.g., if the deflector comprises a MEMS mirror or otherpiezoelectric or thermoelectric mirror, if the deflector comprises anOptical Phased Array (OPA), etc.). The moving of the at least onedeflector may also be implemented for a light source which is combinedwith the at least one deflector. For example, if the LIDAR systemincludes a vertical-cavity surface-emitting laser (VCSEL) array or anyother type of light emitter array, moving the at least one deflector maycomprise modifying the combination of active lasers of the array. Insuch an implementation, the instantaneous position of the deflector maybe defined by a specific combination of active light sources of theVCSEL array (or other type of light emitter array).

In some embodiments, processor 118 may coordinate the at least one lightdeflector and the light source such that, when the at least one lightdeflector is located at a particular instantaneous position, theoutbound path of the light source is at least partially coincident withthe return path. For example, as depicted in FIG. 2B, projected light204 and reflected light 206 are at least partially coincident. In suchembodiments, the at least one deflector may include a pivotable MEMSmirror.

Similarly, in some embodiments, an overlapping part of the outbound pathand the return path may include a common light deflecting element. Forexample, as depicted in FIG. 2B, light deflector 114 directs theprojected light towards field of view 120 and directs the reflectedlight towards sensor 116. In some embodiments, the common lightdeflecting element may be a movable deflecting element (i.e., adeflecting element which can be controllably moved between a pluralityof instantaneous positions). In some embodiments, the overlapping partmay comprise a part of the surface of the common light deflectingelement. Accordingly, in certain aspects, one or more reflections maycover the entire (or almost the entire) area of the common lightdeflecting element even though the projected light does not impinge onthe entire (or almost the entire) area of the common light deflectingelement.

Alternatively or concurrently, the at least one light deflector mayinclude at least one outbound deflector and at least one returndeflector. For example, as depicted in FIG. 2A, outbound deflector 114Adirects the projected light 204 towards field of view 120 while returndeflector 114B directs reflected light 206 back from an object 208within field of view 120. In such an embodiment, processor 118 mayreceive via the at least one return deflector, reflections of a singlelight beam-spot along a return path to the sensor that is not coincidentwith the outbound path. For example, as depicted in FIG. 2A, projectedlight 205 travels along a path not coincident with reflected light 206.

The optical paths, such as the outbound paths and return pathsreferenced above, may be at least partly within a housing of the LIDARsystem. For example, the outbound paths may include a portion of spacebetween the light source and the at least one light deflector and/or mayinclude a portion of space between the at least one light deflector andan aperture of the housing that are within the housing. Similarly, thereturn paths may include a portion of space between the at least onelight deflector (or separate at least one light deflectors) and anaperture of the housing and/or a portion of space between the sensor andthe at least one light deflector (or separate at least one lightdeflectors) that are within the housing.

At step 705, while the at least one deflector is in a particularinstantaneous position, processor 118 receives via the at least onedeflector, reflections of a single light beam-spot along a return pathto a sensor (e.g., at least one sensor 116 of sensing unit 106 of FIGS.1A, 2A, 2B, and 2C). As used herein, the term “beam-spot” may refer to aportion of a light beam from the light source that may generate one ormore reflections from the field of view. A “beam-spot” may comprise asingle pixel or may comprise a plurality of pixels. Accordingly, the“beam spot” may illuminate a part of the scene which is detected by asingle pixel of the LIDAR system or by several pixels of the LIDARsystem; the respective part of the scene may cover the entire pixel butneed not do so in order to be detected by that pixel. Furthermore, a“beam-spot” may be larger in size than, approximately the same size as,or smaller in size than the at least one deflector (e.g., when the beamspot is deflected by the deflector on the outbound path).

At step 707, processor 118 receives from the sensor on abeam-spot-by-beam-spot basis, signals associated with an image of eachlight beam-spot. For example, the sensor may absorb the reflections ofeach beam-spot and convert the absorbed beam-spot to an electronic (orother digital) signal for sending to processor 118. Accordingly, thesensor may comprise a SiPM (Silicon photomultipliers) or any othersolid-state device built from an array of avalanche photodiodes (APD,SPAD, etc.) on a common silicon substrate or any other device capable ofmeasuring properties (e.g., power, frequency) of electromagnetic wavesand generating an output (e.g., a digital signal) relating to themeasured properties.

In some embodiments, the sensor may include a plurality of detectors(e.g., detection elements 402 of detection array 400 of FIG. 4A). Incertain aspects, a size of each detector may be smaller than the imageof each light beam-spot, such that on a beam-spot-by-beam-spot basis,the image of each light beam-spot impinges on a plurality of detectors.Accordingly, as used herein, a plurality of light beam-spots need notinclude all the spots for which images are projected but rather at leasttwo spots that are larger than a plurality of detectors.

In some embodiments, each detector out of a plurality of detectors ofthe sensor may comprise one or more sub-detectors. For example, adetector may comprise a SiPM, which may comprise a plurality ofindividual single-photon avalanche diodes (SPADs). In such an example,the sensor may include a plurality of SiPM detectors (e.g. 5, 10, 20,etc.), and each SiPM may include a plurality of SPADs (e.g. tens,hundreds, thousands). Accordingly, in certain aspects, a detectorcomprises a minimal group whose output is translated to a single datapoint in a generated output model (e.g., a single data point in agenerated 3D model).

In some embodiments, the LIDAR system may include a plurality of lightsources. In such embodiments, processor 118 may concurrently controllight emission of a plurality of light sources aimed at a common lightdeflector. For example, as depicted in FIG. 2B, plurality of lightsources 102 are aimed at a common light deflector 114. Moreover,processor 118 may receive from a plurality of sensors, each locatedalong a differing return path, signals associated with images ofdiffering light beam-spots. For example, as further depicted in FIG. 2B,plurality of sensors 116 receive reflections along differing returnpaths. The plurality of sensors 116 may thus generate signals associatedwith images of differing light beam-spots. In some embodiments, thereflections may also be deflected by at least one scanning lightdeflector. For example, as depicted in FIG. 2B, plurality of scanninglight deflectors 214 deflect reflections received along differing returnpaths before reaching plurality of sensors 116.

In some embodiments, the sensor may include a one-dimensional array ofdetectors (e.g., having at least four individual detectors). In otherembodiments, the sensor may include a two-dimensional array of detectors(e.g., having at least eight individual detectors).

At step 709, processor 118 determines, from signals resulting from theimpingement on the plurality of detectors, at least two differing rangemeasurements associated with the image of the single light beam-spot.For example, the at least two differing range measurements maycorrespond to at least two differing distances. In a similar example,the sensor may be configured to detect reflections associated with atleast two differing times of flight for the single light beam-spot. Insuch an example, a time of flight measurement may differ on account ofthe difference in distance traveled for the light beam-spot with respectto the different detectors. Similarly, a frequency phase-shiftmeasurement and/or a modulation phase shift measurement may differ onaccount of the difference in distance and/or angle of incidence withrespect to the different detectors.

In some embodiments, the at least two differing range measurements maybe derived from detection information acquired by two or more detectorsof the sensor(s) (e.g., two or more independently sampled SiPMdetectors). In addition, the at least two differing range measurementsmay be associated with two differing directions with respect to theLIDAR system. For example, a first range measurement detected by a firstdetector of the sensor(s) may be converted to a first detection location(e.g., in spherical coordinates, θ₁, ϕ₁, D₁), and the second rangemeasurement detected from reflections of the same beam spot by a seconddetector of the sensor(s) may be converted to a second detectionlocation (e.g., in spherical coordinates, θ₂, ϕ₂, D₂), where anycombination of at least two pairs of coordinates differ between thefirst detection location and the second detection location (e.g. θ₂≠θ₂and D₁≠D₂ or the like).

In another example in which the at least two differing rangemeasurements correspond to at least two differing distances, the atleast two differing range measurements may include a first distancemeasurement to a portion of an object and a second distance measurementto an element in an environment of the object. For example, if thebeam-spot covers both an object (such as a tree, building, vehicle,etc.) and an element in an environment of the object (such as a road, aperson, fog, water, dust, etc.), the first range measurement mayindicate a distance to a portion of the object (such as a branch, adoor, a headlight, etc.), and the second range measurement may indicatea distance to the background element. In yet another example in whichthe at least two differing range measurements correspond to at least twodiffering distances, the at least two differing range measurements mayinclude a first distance measurement to a first portion of an object anda second distance measurement to a second portion of the object. Forexample, if the object is a vehicle, the first range measurement mayindicate a distance to a first portion of the vehicle (such as a bumper,a headlight, etc.), and the second range measurement may indicate adistance to a second portion of the vehicle (such as a trunk handle, awheel, etc.).

Alternatively or concurrently, the at least two differing rangemeasurements associated with the image of the single light beam-spot maycorrespond to at least two differing intensities. Similarly, then, theat least two differing range measurements may include a first intensitymeasurement associated with a first portion of an object and a secondintensity measurement associated with a second portion of the object.

In some embodiments, processor 118 may concurrently determine a firstplurality of range measurements associated with an image of a firstlight beam-spot and a second plurality of range measurements associatedwith an image of a second light beam-spot. In certain aspects, the firstplurality of range measurements may be greater than the second pluralityof range measurements. For example, if the first light beam-spotincludes more detail than the second light beam-spot, processor 118 maydetermine more range measurements from the first light beam-spot thanfrom the second light beam-spot. In such an example, measurements fromthe first light beam-spot may comprise 8 measurements, and measurementsfrom the second light beam-spot may comprise 5 measurements if, forexample, the second light beam-spot is directed to or includes at leastpartially the sky.

In some embodiments, a number of differing range measurements determinedin the scanning cycle may be greater than the plurality of instantaneouspositions. For example, processor 118 may determine at least twodiffering range measurements for each instantaneous position, asexplained above with reference to step 709. For example, if the sensorincludes N detectors, and the LIDAR system detects ranges in Minstantaneous positions of the deflector in each scanning cycle, thenumber of range measurements determined may be up to N×M. In someembodiments, the number of emitted pulses in each scanning cycle may belower than the number of generated point-cloud data points (or other 3Dmodel data points) even when a number of pulses is emitted for eachportion of the FOV. For example, if P pulses are emitted in eachinstantaneous position, the number of pulses may be P×M for a scanningcycle, and, in the embodiments described above, P<M.

Method 700 may include additional steps. For example, method 700 mayinclude generating output data (e.g., a 3D model) in which the differingmeasurements are associated with different directions with respect tothe LIDAR. In such an example, processor 118 may create a 3D-model frame(or the like) from the information of different light beams and manypixels from different angles of the FOV.

In certain aspects, the different directions may differ with respect toan optical window or opening of the LIDAR through which reflectedsignals pass on their way to the at least one detector. For example, inspherical coordinates, at least one of ϕ or θ may be different betweenthe two measurements.

In some embodiments, method 700 may further include generating aplurality of point-cloud data entries from reflections of the singlelight beam-spot. For example, processor 118 may generate a plurality ofpoint-cloud data entries like those depicted in FIG. 1B from thereflections of the single light beam-spot. Processor 118 may generate aplurality, such as 2, 3, 4, 8, or the like from the single lightbeam-spot, e.g., using the at least two range measurements from step709.

The plurality of point-cloud data entries may define a two-dimensionalplane. For example, the plurality of point-cloud data entries may form aportion of a point-cloud model, like that depicted in FIG. 1C.

Method 700 may be performed such that different portions of the field ofview are detected at different times. Accordingly, one portion of thefield of view may be illuminated and result in the determination of aplurality of range measurements while at least one other portion of thefield of view is not illuminated by the light source. Accordingly,method 700 may result in a scan of a portion of the field of view, whichis then repeated for a different portion of the field of view, resultingin a plurality of “scans within a scan” of the field of view, asdepicted in the examples of FIGS. 10B and 10C.

As explained above, FIG. 4C is a diagram illustrating an example of atwo-dimensional sensor 116 that may be used in method 700 of FIG. 7.FIG. 8A depicts an alternative sensor 800 for use in lieu of or incombination with sensor 116 of FIG. 4C. For example, detectors 410 inthe example of FIG. 4C are rectangular while the example of FIG. 8Adepicts a plurality of hexagonal pixels (e.g., pixels 844) comprised ofindividual detectors (such as detectors 846). Similarly, FIG. 8B depictsan alternative one-dimensional sensor 850 for use in lieu of or incombination with sensor 116 of FIG. 4C and/or sensor 800 of FIG. 8A. Inthe example of FIG. 8B, a one-dimensional column of pixels (e.g., pixel854) is comprised of individual detectors (such as detector 856).Although depicted as a one-dimensional vertical column in FIG. 8B,another embodiment may include a one-dimensional horizontal row ofdetectors.

FIGS. 9A and 9B are block diagrams illustrating example LIDAR deviceshaving alignment of transmission and reflection. LIDAR systems 900 and900′ of FIGS. 9A and 9B represent implementations of LIDAR system 100 ofFIG. 1. Accordingly, functionality and modifications discussed withrespect to FIGS. 1A-C may be similarly applied to the embodiments ofFIGS. 9A and 9B and vice versa. For example, as depicted in FIGS. 9A and9B, LIDAR 900 and 900′ may include at least one photonic pulse emitterassembly 910 for emitting a photonic inspection pulse (or pulses).Emitter 910 may include projecting unit 102 with at least one lightsource 112 of FIG. 1A, 2A, or 2B.

As further depicted in FIGS. 9A and 9B, LIDAR 900 and 900′ may includeat least one photonic steering assembly 920 for directing the photonicinspection pulse in a direction of a scanned scene segment, and forsteering the reflected photons towards photonic detection assembly 930.Steering assembly 920 may include controllably steerable optics (e.g. arotating/movable mirror, movable lenses, etc.) and may also includefixed optical components such as a beam splitter. For example,deflectors 114A and 114B of FIG. 2A and/or common light deflector 114and plurality of scanning light deflectors 214 of FIG. 2B may beincluded in steering assembly 920. Some optical components (e.g., usedfor collimation of the laser pulse) may be part of emitter 910, whileother optical components may be part of detector 930.

In FIGS. 9A and 9B, LIDAR 900 and 900′ may further include at least onephotonic detection assembly 930 for detecting photons of the photonicinspection pulse which are reflected back from objects of a scannedscene. Detection assembly 930 may, for example, include atwo-dimensional sensor 932, such as sensor 116 of FIG. 4C and/or sensor800 of FIG. 8. In some embodiments, detection assembly 930 may include aplurality of two-dimensional sensors.

As depicted in FIGS. 9A and 9B, LIDAR 900 and 900′ may include acontroller 940 for controlling the steering assembly 920, and/or emitter910 and/or detector 930. For example, controller 940 may include atleast one processor (e.g., processor 118 of processing unit 108 of LIDARsystem 100 as depicted in FIG. 1A and/or two processors 118 ofprocessing unit 108 of the LIDAR system depicted in FIG. 2A). Controller940 may control the steering assembly 920, and/or emitter 910 and/ordetector 930 in various coordinated manners, as explained both above andbelow. Accordingly, controller 940 may execute all or part of themethods disclosed herein.

As depicted in FIG. 9B, LIDAR 900′ also includes at least one visionprocessor 950. Vision processor 950 may obtain collection data fromphotonic detector 930 and may process the collection data in order togenerate data therefrom. For example, vision processor 950 (optionallyin combination with controller 940) may generate point-cloud dataentries from the collection data and/or generate a point-cloud datamodel therefrom.

In both LIDAR 900 and 900′, transmission (TX) and reflection (RX) arecoordinated using controller 940 (and optionally visional processor 950for LIDAR 900′). This coordination may involve synchronized deflectionof both transmission and reflection using coordination amongst aplurality of light deflectors and/or synchronized deflection of bothtransmission and reflection using coordination within a shareddeflector. The synchronization may involve physical movement and/orpiezoelectrical/thermoelectrical adjustment of the light deflector(s).

FIG. 10A illustrates an example first FOV 1000 and several examples ofsecond FOVs 1002 and 1004. The angular sizes and pixel dimensions of anyFOV may differ than the examples provided in FIG. 10A.

FIG. 10B illustrates an example scanning pattern of second FOV 1002 ofFIG. 10A across first FOV 1000 of FIG. 10A. As depicted in FIG. 10B,second FOV 1002 may be scanned and then moved right-to-left in ahorizontal pattern followed by left-to-right in a diagonal patternacross FOV 1000. Such patterns are examples only; systems and methods ofthe present disclosure may use any patterns for moving a second FOVacross a first FOV.

FIG. 10C illustrates an example scanning pattern of a second FOV 1006across first FOV 1000 of FIG. 10A. As depicted in FIG. 10C, second FOV1006 may be scanned and then moved right-to-left in a horizontal patternacross FOV 1000. Such a pattern is an example only; systems and methodsof the present disclosure may use any patterns for moving a second FOVacross a first FOV. Referring to the examples of FIGS. 10B and 10C, itis noted that the array sizes used in the diagrams are used asnon-limiting examples only, just like the non-limiting example of FIG.10A, and that the number of pixels in each array can be significantlylower (e.g., 2×3, 3×5, etc.), significantly higher (e.g., 100×100,etc.), or anywhere in between.

In the example of FIG. 10C, second FOV 1006 has a height correspondingto the height of first FOV 1000. Accordingly, as shown in FIG. 10C, bymatching at least one corresponding dimension of the second FOV with thefirst FOV, a lower scan rate of the second FOV across the first FOV maybe required. Accordingly, LIDAR systems consistent with the presentdisclosure may include a 1D sensor array whose dimension corresponds toat least one dimension of the first FOV.

Returning to the example of FIG. 10B, the second FOV 1002 is smaller inboth dimensions than the first FOV 1000. This may allow the LIDAR systemto concentrate more energy at a smaller area, which may improve thesignal-to-noise ration and/or a detection distance.

By scanning a second FOV across a first FOV, systems of the presentdisclosure may allow for generation of a 3D model with relatively lowsmear of objects, in part because larger parts of the objects may bedetected concurrently by the steerable 2D sensor array. The reducedsmear level may be achieved across one or more of the axes of the sensorarray (e.g., (X,Y), (ϕ,θ)), and/or across the depth axis (e.g., Z, r).The low level of smear may result in higher detection accuracy.

Scanning a second FOV across the first FOV may further allow scanning ina relatively low frequency (e.g., moving the mirror at the vertical axisat about 10 times lower frequency if 10 vertical pixels are implementedin the sensor array). A slower scanning rate may allow utilization of alarger mirror.

Scanning a second FOV across the first FOV may further allow the use ofa weaker light source than in extant systems, which may reduce powerconsumption, result in a smaller LIDAR system, and/or improve eye safetyand other safety considerations. Similarly, scanning a second FOV acrossthe first FOV may allow for the use of a relatively small sensor ascompared with extant systems, which may reduce size, weight, cost,and/or complexity of the system. It may also allow for the use of a moresensitive sensor than in extant systems.

Scanning a second FOV across the first FOV may further allow thecollection of less ambient light and/or noise. This may improve thesignal-to-noise ration and/or a detection distance as compared withextant systems.

Selective Illumination in Lidar Based on Detection Results

As noted above, LIDAR system 100 may be used to generate depth maps ofdetected objects within a scene. Such depth maps may include point cloudmodels, polygon meshes, depth images, or any other type of 3D model of ascene. In some cases, however, less than all of the objects in aparticular scene, or within a particular distance range, may be detectedby the LIDAR system. For example, while objects relatively close to theLIDAR system may be detected and included in a 3D reconstruction of ascene, other objects (e.g., including objects that are smaller, lessreflective, or farther away, etc.) may go undetected for a particularset of operational parameters of the LIDAR system. Additionally, asignal to noise ratio of the system, in some instances, may be less thandesirable or lower than a level enabling detection of objects in a fieldof view of the LIDAR system.

In certain embodiments, the presently described LIDAR system, includingany of the configurations described above, may enable variation of oneor more operational parameters of the LIDAR system during a current scanof an FOV or during any subsequent scan of the FOV in order todynamically vary light flux amounts to different sections of the LIDARFOV. In doing so, LIDAR system 100 may offer an ability to increase anumber of detected objects within the FOV. LIDAR system 100 may alsoenable increases in signal to noise ratios (e.g., a ratio ofillumination from the LIDAR system compared with other sources of noiseor interference, such as sun light (or other sources of illumination)and electrical noise associated with detection circuitry, for example).Increasing the signal to noise ratio can enhance system sensitivity andresolution. Through such dynamic variation of light flux provided atdifferent regions of the LIDAR FOV, depth maps (or other representationsof a scene) from an environment of the LIDAR system may be generated,that include representations of one or more objects that may haveotherwise gone undetected.

While there are many different possibilities for dynamically alteringlight flux to certain areas of a scanned FOV, several examples of whichare discussed in more detail below, such dynamic variation of light fluxmay include reducing or maintaining a light flux level where objects aredetected within the scanned FOV and increasing light flux in regionswhere objects are not detected. Such increases in light flux may enabledetection of more distant objects or less reflective objects. Suchincreases in light flux may also enhance the signal to noise ratio in aparticular region of the scanned FOV. As noted, these effects may enablegeneration of a depth map of objects in an environment of the LIDARsystem that offers more complete information. In addition to objectsdetectable within a certain range associated with a fixed light fluxscan, the system may also identify other objects through dynamicadjustment of light flux during scanning.

As noted above, LIDAR system 100 may include a projecting unit 102,including at least one light source 112. Processing unit 108 may beconfigured to coordinate operation of light source 112 and any otheravailable light sources. In some cases, processing unit 108 may controllight source 112 in a manner enabling light flux to vary over a scan ofa field of view of the LIDAR system using light from the at least onelight source 112. Processing unit 108 may also control deflector 114 ofscanning unit 104 in order to deflect light from the at least one lightsource 112 in order to scan the field of view. And as previouslydescribed, processing unit 108 may interact with sensing unit 106 inorder to monitor reflections from various objects (e.g., based onsignals generated by one or more sensors on which the reflections areincident) in the scanned FOV. Based on the monitored reflections,processing unit 108 may generate depth maps or other reconstructions ofa scene associated with the scanned FOV. For example, processing unit108 may use first detected reflections associated with a scan of a firstportion of the field of view to determine an existence of a first objectin the first portion at a first distance. During the scan of the FOV,processing unit 108 may determine an absence of objects in a secondportion of the field of view at the first distance. For example,processing unit 108 may determine the absence of objects in the secondportion by processing sensor detection signals received over a period oftime that corresponds with or includes the travel time of light along adistance equal to twice the first distance (as reflected light needs totravel to and back from an object, if one exists within the firstrange), as measured beginning with the emission of light towards thesecond portion of the field of view. Following the detection of thefirst reflections and the determination of the absence of objects in thesecond portion, the processing unit 108 may alter a light sourceparameter associated, for example, with the at least one light source112 such that more light is projected toward the second portion of thefield of view than is projected toward the first portion of the field ofview. The processing unit 108 may also use second detected reflectionsin the second portion of the field of view to determine an existence ofa second object at a second distance greater than the first distance.

During a scan of the LIDAR system FOV, processor unit 108 may controlone or more parameters associated with the available light sources 112in order to change an amount of light flux provided (e.g., projected) tocertain regions of the FOV. In some cases, the change in light flux mayinclude an increase in light flux in one region of the FOV relative toan amount of light flux provided in another region of the FOV. Thechange in light flux may also include an increase in an amount of lightprovided over a particular time period relative to another time period(e.g., within a particular region of the FOV). An increase in light fluxcorresponding to more light being projected or supplied to a particularregion may include various quantitative characteristics of projectedlight. For example, an increase in light flux may result in or may beassociated with a corresponding increase in: power per solid angle,irradiance versus FOV portion, a number of projected light pulses, powerper pixel, a number of photons per unit time, a number of photons perscan cycle, aggregated energy over a certain period of time, aggregatedenergy over a single scan cycle, flux density (e.g. measured in W/m²), anumber of photons emitted per data point in a generated point cloudmodel, aggregated energy per data point in a generated point cloudmodel, or any other characteristic of increasing light flux.

The deflector 114 controlled by processing unit 108 to deflect the lightfrom the at least one light source 112 may include any suitable opticalelement for changing an optical path of at least a portion of lightincident upon the deflector. For example, in some embodiments, deflector114 may include a MEMS mirror (e.g., a pivotable MEMS mirror). Thedeflector may include other types of mirrors, prisms, controllablelenses, mechanical mirrors, mechanical scanning polygons, activediffraction elements (e.g., a controllable LCD), Risley prisms, anon-mechanical electro optical beam steerer, polarization gratings, anoptical phased array (OPA), or any other suitable light steeringelement.

Optionally, after the first object is detected, processing unit 108 maycontrol the at least one light source 112 and/or the at least onedeflector such that all of the emissions toward the second region of theFOV used in the detection of the second object are emitted beforeadditional light is emitted to the first portion (e.g. at a later scancycle).

This technique of scanning a LIDAR FOV and dynamically varying lightflux provided to certain regions of the LIDAR FOV will be described inmore detail with respect to FIGS. 11 and 12. FIG. 11 provides adiagrammatic illustration of an FOV 120 that may be scanned usingprocessing unit 108 to control the one or more light sources 112 and theat least one deflector 114. For example, as previously described, theFOV may be scanned by moving deflector 114 through a plurality ofinstantaneous positions, each corresponding with a particular portion122 of FOV 120. It is noted that FOV 120 may include a plurality ofsubstantially equal-sized portions 122 (e.g. defined by the same solidangle). However, this is not necessarily so. It should be noted thatduring a scan of FOV 120, deflector 114 may dwell at each instantaneousposition for a predetermined amount of time. During that time, light maybe projected to a corresponding portion 122 of FOV 120 in a continuouswave, a single pulse, multiple pulses, etc. Also, during thepredetermined dwell time at a particular instantaneous position, lightreflected from objects in a scene may also be directed to one or moredetector units using deflector 114 (e.g., in monostatic embodiments).Alternatively, deflector 114 may move continuously (or semicontinuously) through a plurality of instantaneous positions during ascan of FOV 120. During such a continuous or semi-continuous scan, lightmay be projected to instantaneous portions 122 of FOV 120 in acontinuous wave, a single pulse, multiple pulses, etc. Also, during sucha continuous or semi-continuous scan, light reflected from objects in ascene may also be directed to one or more detector units using deflector114 (e.g., in monostatic embodiments).

A scan of FOV 120 may progress, for example, by projecting light fromlight source 112 to region 1102 of FOV 120, collecting reflected lightfrom region 1102, and performing time of flight analysis based on theprojected and reflected light to determine distances to one or moreobjects within region 1102 that produced the reflections. Aftercollecting the reflected light from region 1102, processing unit 108 maycause deflector 114 to move to another region of FOV 120 (e.g., anadjacent region or some other region) and repeat the process. The entireFOV 120 may be scanned in the manner (e.g., moving from region 1102 to1104 and then scanning all additional rows to end at region 1106). Whilethe scanning pattern associated with FIG. 11 may be from left to rightand then right to left for each successive row beginning at the top row,any suitable scanning pattern may be used for scanning FOV 120 (e.g.,row by row in either or both horizontal directions; column by column ineither or both vertical directions; diagonally; or by selection of anyindividual regions or a subset of regions). And as also describedpreviously, depth maps or any type of reconstruction may be generatedbased on the reflections and distance to object determinations.

Processing unit 108 may control deflector 114 in any suitable manner forenabling deflector 114 to redirect light from light source 112 tovarious regions 122 of FOV 120. For example, in some embodiments, the atleast one processor 118 may be configured to control the at least onelight deflector 114 such that the at least one light deflector ispivoted in two orthogonal axes or along two substantially perpendicularaxes. In other embodiments, the at least one processor 118 may beconfigured to control the at least one light deflector 114 such that theat least one light deflector is pivoted along two linearly independentaxes, which may enable a two-dimensional scan. Such deflector movementmay be obtained by any of the techniques described above. Additionally,in some cases, processing unit 108 may control a rotatable motor forsteering the at least one light deflector.

As the scan of FOV 120 progresses, light reflections from some of theparticular regions in the FOV (e.g., regions 122) may be used todetermine an existence of an object within a particular region of theFOV. For example, during the scan of region 1108, reflections receivedfrom car 1110 may enable processing unit 108 to determine the presenceof an object (i.e., the car) within region 1108 and also to determine adistance to that object. As a result of a scan of region 1108,processing unit 108 may determine that an object exists within thatregion and that the object resides at a distance, D1, relative to a hostof the LIDAR system 100. It is noted that optionally, processing unit108 may determine more than a single distance for a region of the FOV.This may occur, for example, if two or more objects are reflecting lightin the same FOV (e.g. in region 1120 of FIG. 12, reflections from bothcar 1202 and the road may be received and analyzed), or if thereflective object is positioned in a way which reflects light from arange of distances (e.g., from a slanted surface).

Scans of other regions of FOV 120, however, may not result in the returnof observable reflections. In such cases, processing unit 108 will notdetect the presence of objects within those regions. For example,regions 1120 and 1122 of FOV 120, as illustrated in FIG. 11, have notreturned observable reflections during the respective scans of thoseregions. As a result, a depth map created based on reflections receivedand distance analysis performed for the regions of FOV 120 will not showthe presence of any objects within regions 1120 or 1122. Processing unit108 may determine, based on the absence of available reflections inregions 1120 and 1122 (and other non-reflecting regions) that there isan absence of objects in those regions at a range of distances at whichLIDAR system 100, for a given set of operational parameters, issensitive. For example, because processing unit 108 may determine thatcar 1110 (or at least a portion of the car) is present at a distance D1in region 1108, based on reflections received from that region,processing unit 108 may determine that no objects are present in region1120 at distance D1 relative to LIDAR system 100. This determination maybe based on the presumption that had any objects been present in region1120 at a distance D1 (and assuming such objects had reflectivitycharacteristics similar to car 1110), processing unit 108 would haveidentified the presence of those objects as it did in region 1108.

Notably, a determination of an absence of objects in a particular regionof FOV 120 may be based on the detection capabilities of the LIDARsystem for a particular set of operational parameters. Changing of thoseoperational parameters, especially in a manner that may increase adetection sensitivity of the LIDAR system (e.g., increasingsignal-to-noise ratio), may result in an identification of objects inregions where no objects were detected prior to changing the operationalparameters.

In regions of the FOV where processing unit 108 determines an absence ofobjects at distance D1 (e.g., regions 1120 or 1122), processing unit 108may alter a light source parameter such that more light is projectedtoward one or more regions of the FOV than is projected toward regionsof the FOV where objects are detected. With respect to the example shownin FIG. 11, after not detecting any objects in region 1120 (either atdistance D1 or otherwise), processing unit 108 may alter a light sourceparameter such that more light is projected to region 1120 than wasdirected to region 1108 (where a portion of car 1110 was detected). Suchan increase in an amount of light provided to region 1120 may increasethe signal-to-noise ratio in that area, may increase the LIDAR systemsensitivity in that region, may enable the system to detect objectshaving lower reflectivity, and/or may enable the system to detectobjects that may be located farther away (e.g., at distances greaterthan D1).

Various light source parameters may be altered in order to cause anincrease in an amount of light supplied to a particular region of theFOV. For example, processing unit 108 may cause light source 112 toincrease a duration of a continuous wave emission, increase a totalnumber of light pulses, increase an overall light energy of emittedlight, and/or increase the power (e.g., peak power, average power, etc.)of one or more light pulses projected to a particular region of the FOV.Additionally or alternatively, a light-pulse-repetition number per scanmay be increased such that more light pulses are supplied to one regionof the FOV as compared to another region of the FOV. More broadly, afterdetermining the absence of objects in a particular region at aparticular distance or range of distances, for example, or based on anyother criteria relating to detection results relative to a certainregion of the FOV, any light source parameter may be adjusted such thatthe flux of light directed to one portion of the field of view (e.g.,region 1120) is different (e.g., greater) than the flux of lightdirected to another portion of the field of view (e.g., region 1108). Aspreviously noted, references to more light being projected to aparticular region may include at least one of: additional power providedper solid angle, increased irradiance relative to a portion size,additional pulses of light, more power per pixel, more photons for agiven period of time, an increase in aggregate of energy over apredefined time period, higher flux density, W/m², a larger number ofphotons per scan cycle, more aggregated energy over a certain period oftime, more aggregated energy over a single scan cycle, a larger numberof photons emitted per data point in a generated point cloud model, moreaggregated energy per data point in a generated point cloud model, etc.

Alteration of the various light source parameters may occur in responseto any observed criteria. For example, at least one pilot pulse may beemitted, and detection results may be observed based on acquiredreflections of the at least one pilot pulse. Where the detection resultsfor a particular region in which the at least one pilot pulse wasemitted indicate no objects present, no objects present at a particulardistance (e.g., D1), fewer than expected objects present, no objectsdetected beyond a particular distance range, low reflectivity objectsdetected, low signal to noise ratios (or any other suitable criteria),then processing unit 108 may cause more light to be supplied to theparticular region using any of the techniques described above (longercontinuous wave, added pulses, higher power, etc.), or any othertechnique resulting in more light being supplied to the particularregion. In some cases, a “pilot pulse” may refer to a pulse of lightwhose detected reflections are intended for deciding upon followinglight emissions (e.g., to the same region of the FOV, during the samescan). It is noted that the pilot pulse may be less energetic thanpulses of the following light emissions, but this is not necessarily so.In some cases, a pilot pulse may correspond to any initial light pulse(in an emission sequence) provided to a particular region of the LIDARFOV.

The alteration of the various light source parameters may also occur aspart of a predetermined operational sequence. For example, in someembodiments, a predetermined illumination sequence for one or more ofthe regions 122 of the FOV 120 may include providing a specified seriesof light pulses toward one or more of the regions 122 of FOV 120. Afirst light pulse may include a relatively low power, and one or moresubsequent pulses may include a higher power level than the firstemitted pulse. In some cases, the light pulses may be emitted withprogressively increasing power levels. It is nevertheless noted that theseries of pulses may be of similar per-pulse power levels, and theincrease in light amount is achieved in the accumulative emitted amountduring the scan.

Increases in light amounts provided to a particular region of the FOVmay occur at various times during operation of LIDAR system 100. In someembodiments, the increases in light supplied to a particular regionversus another region of the FOV may occur during a current scan of theFOV. That is, during a particular scan of the FOV, an amount of lightsupplied to a portion of the FOV associated with a particularinstantaneous position of deflector 114 may be greater than an amount oflight provided to a portion of the FOV corresponding to a differentinstantaneous position of deflector 114 during the particular scan ofthe FOV. Thus, in some embodiments, processing unit 108 may beconfigured to alter the light source parameter such that more light(e.g., more irradiance per solid angle) is projected toward a particularregion of the FOV in a same scanning cycle in which an absence ofobjects was determined (e.g., at a particular distance) in other regionof the FOV.

Alternatively, increases in light supplied to a particular FOV region ascompared to another region of the FOV may occur during different scansof the FOV. In other words, a complete scan of the FOV may be performed,and on subsequent scans of the FOV, more light may be supplied to one ormore regions of the FOV as compared to other regions of the FOV based onthe results of the previous scan of the FOV. In some cases, it may notbe necessary to do a complete scan of the FOV before returning to aparticular portion of the FOV and increasing the amount of lightsupplied to the particular region relative to an amount of lightsupplied to another portion of the FOV. Rather, such an increase mayoccur even after a partial scan of the FOV before returning to aparticular region of the FOV and increasing an amount of light suppliedthere, either relative to an amount of light that was supplied to thatregion during a previous scan (or partial scan) or relative to an amountof light provided to another region of the FOV.

An increase in an amount of light supplied to a particular region of theFOV, such as region 1120, may result in additional reflections fromwhich object detection may be possible. In view of the increased amountof light supplied to the particular region, it may be possible toincrease the signal to noise ratio for light collected from that region.As a result of an improved signal to noise ratio and/or in view ofadditional light available for detection (including, at least in someinstances, higher power light) it may be possible to detect the presenceof objects at distances further from the LIDAR system than what waspossible based the use of lower amounts of light in a particular FOVregion.

As an illustrative example, in some embodiments a scan of FOV 120 inFIG. 11 may commence using a predetermined or default amount of lightsupplied to each specific region 122 of the FOV. If an object isdetected in a particular region, such as region 1108, for example, thenprocessing unit 108 may move deflector 114 to another instantaneousposition in order to examine another area of FOV 120, without additionallight being emitted to the aforementioned region (e.g. region 1108).Where no objects are detected in a particular region, such as region1120, processing unit 108 may cause an additional amount of light to besupplied to that region. The increased amount of light may be providedduring a current scan of the FOV and before deflector 114 is moved to anew instantaneous position. Alternatively, the increase in an amount oflight, e.g., to region 1120, may be made during a subsequent scan orpartial scan of FOV 120. In some cases, the increase in the amount oflight supplied to a region, such as region 1120 may result in thedetection of objects that were not detected during examination of theparticular FOV region using a lower amount of light. An example in whichadditional light is provided during a partial scan of the FOV 120 isthat pilot pulses are emitted to each region of a row while scanning ina first direction, and additional light is emitted while scanning backin the opposite directions to regions in which absence of objects weredetermined, and only than a scanning of another row is initiated.

In the illustrative example, if based on one or more pilot pulse noobject is detected in region 1120 or no objects are detected in region1120 beyond a certain distance (e.g., distance D1 at which car 1110 wasdetermined to be located), then an amount of light may be increased toregion 1120 using any of the previously described techniques. Forexample, in one embodiment, one or more additional light pulses(optionally, at higher power levels than the pilot pulse) may beprovided to region 1120. These additional light pulses may each resultin subsequent reflections detectable by sensing unit 106. As a result,as shown in FIG. 12, an object, such as a car 1202, may be detected. Insome cases, this object, such as car 1202, may be located at a distanceD2 greater than a distance at which objects were previously detected inthe same region or in different regions (e.g., car 1110 located at adistance D1 and occupying region 1108 and nearby regions of the FOV).Thus, in the specific (and non-limiting) illustrative example, aninitial pilot pulse of light provided to region 1120 and its subsequentreflection may not result in detection of any objects at a distanceD1—the distance at which car 1110 was detected in region 1108 based on apilot pulse, e.g., provided to region 1108. In response to an observedabsence of objects at distance D1 in region 1120, one or more additionalpulses (optionally higher powered pulses or a lengthened continuouswave, etc., but not necessarily so) may be supplied to region 1120 inorder to provide more light to region 1120. Based on these one or moreadditional pulses provided to region 1120 and their respective,subsequent reflections, the existence of an object, such as car 1202,may be determined at a distance D2 greater than distance D1, where car1110 was detected in region 1108.

It should be noted that an increase in an amount of light and thespecific protocol selected for providing the increase in the amount oflight may be unique to a particular region of the FOV, such as region1120, which may correspond to a particular instantaneous position ofdeflector 114. Alternatively, a specific protocol selected forincreasing light may not be limited to a particular region of the FOV,such as region 1120, but rather may be shared by a plurality of regionsof the FOV. For example, region 1204 of FOV 120 (surrounded by dashedlines in FIG. 12) may include four particular regions of the FOV eachcorresponding to a different instantaneous position of deflector 114. Insome embodiments, a selected protocol for increasing light to any of thesub-regions of FOV region 1204 may be the same across all of thesubregions. As a result, application of a common light-increasingprotocol to each of the sub-regions of FOV region 1204 may result inmultiple objects or a single object being detected in the sub-regions atsimilar distances or distance ranges. For example, as shown in FIG. 12,through application of a common light-increasing protocol across thesub-regions of FOV region 1204, portions of car 1202 (e.g., at adistance D2 greater than a distance D1 where car 1110 was detected) maybe detected in each of the different sub-regions of FOV region 1204. Itshould be noted, optionally the decision of whether to increase lightemission in one region of the FOV may be dependent (at least in part) onreflection detection information of another region of the FOV.

In addition to providing an ability to detect more distant objectsthrough addition of light to a particular region of the FOV, otherobjects may also be detected as a result of the increase in light. Forexample, as shown in FIG. 11, a pilot pulse of light supplied to region1122 may not result in detection of any objects in region 1122. Asubsequent increase in light supplied to region 1122 and at least oneresulting reflection, however, may enable detection of an object inregion 1122, such as a turtle 1206, as shown in FIG. 12. While turtle1206 may be located at a distance D3 less than D1 (e.g., closer to theLIDAR system than car 1110), turtle 1206 may have a lower reflectivitythan car 1110 and, therefore, may have gone undetected in response tothe initial pilot pulse supplied to region 1122 (the lower reflectivityof turtle 1206 may be a result, for example, of its partial sizerelative to region 112 and/or of the lower reflectivity factor of itsshell). One or more subsequent light pulses, for example, provided toregion 1122 along with their respective reflections may enable detectionof the lower reflectivity turtle 1206. Such an approach of increasinglight to regions of the FOV may enable detection of various objects notdetected based on an initial amount of light supplied to a region of theFOV. For example, objects such as distant curbs 1208 and 1210 and/or ahorizon 1212 (at distance D4 greater than D1, D2, and D3) of a road 1214may be detected using this technique. At the same time, for regions ofthe FOV where objects such as car 1110 or tree 1216 are detected usingan initial pulse (or a portion of an available light budget), additionallight increases may not be needed, and the FOV scan may be continued ata different instantaneous position of deflector 114.

While deflector 114 may be moved to a new instantaneous position withoutfurther light emission after detecting an object in a particular regionof the FOV, in some cases, additional light may be emitted while thedeflector still directs light toward the corresponding particular regionof the FOV. Reflections resulting from the supplemental light canprovide further information about the particular region of the FOVand/or confirm detections made based on lower levels of light providedto the same region. For example, in the illustrative example of FIGS. 11and 12, deflector 114 may be positioned in order to provide a pilotpulse to region 1120. A resulting reflection may not result in detectionof any objects in region 1120. Next, a second pulse may be provided toregion 1120 (e.g. at a higher power level than the pilot pulse). Areflection from the second pulse may enable detection of car 1202 at adistance D2 greater than a distance D1 at which car 1110 was detectedbased on a reflection of a pilot pulse provided to region 1108. Ratherthan moving on from region 1120 after detecting car 1202 in that region,however, deflector 114 may remain in its instantaneous positioncorresponding to region 1120. A third pulse (optionally at a higherpower than the second pulse) may be provided to region 1120. Asubsequent reflection of the third pulse may not result in the detectionof any additional objects in region 1120 (although it could). But, thereflection of the third pulse may enable confirmation of thedetermination (e.g., based on the reflection of the second pulse) thatno objects are present in region 1120 at distance D1. The reflection ofthe third pulse may also enable confirmation of the detection of car1202 at distance D2, as determined based on the reflection of the secondpulse supplied to region 1120. It is noted that possibly, none of thereflections of the first, second and third pulses may enable detectionof an object in the respective region, while a combination of all of thereflections could. This may be the result of SNR improvement. Anotherexample would be decision algorithms, which may check for consistency indetection across several pulses.

It should be noted that increases in an amount of light provided to aparticular region of FOV 120, whether relative to amounts of lightprovided to other regions of the FOV or relative to an amount of lightprovided to the particular region of the FOV during the same or earlierscan of the FOV, may proceed according to any desired protocol. Such aprotocol may be applicable to all regions in the FOV, some of theregions of the FOV, or a single region of the FOV. A protocol forselectively increasing light to any portion of the FOV may bepredetermined or may be developed during a scan of the FOV, based, forexample, on various criteria encountered during the FOV scan (e.g.,detection of objects in a particular region, etc.). Where objects aredetected in a particular region as a result of a particular projectedlight amount, during subsequent scans of the FOV, a similar amount oflight may be provided to the particular region. Such an approach mayspeed object detection and scans of the FOV by potentially eliminating aneed to search for objects using increasing amounts of light. In somecases, however, it may be desirable to return to an application of lowerlevels of light to a particular FOV region in subsequent scans of theFOV. For example, where the LIDAR system is moving toward a previouslydetected object, it may be possible to detect the object again, not atthe higher light amount used for its original detection, but insteadusing a lower amount of light.

By varying amounts of light provided to different regions during a scanof the LIDAR system FOV, the detection capability and/or resolution ofthe LIDAR system may be improved. And based on the objects detected ineach of the different regions of the FOV, a three-dimensional map orreconstruction of the scene associated with the FOV may be generatedusing any suitable technique. For example, in some embodiments, a pointcloud may be generated that shows some or all of the detected objectswithin the FOV. Returning to the example of FIG. 12, the point cloud (orother 3D construction) may show car 1110 at distance D1, car 1202 atdistance D2, and turtle 1206 at distance D3, where D3<D1<D2. Eachdetected object represented in the 3D construction may be associatedwith a particular detection direction (ϕ\θ or x\y) or range of angles.

The selective emission of light towards different parts of the FOV basedon detection of objects and absence of objects in the different parts ofthe FOV may allow LIDAR system 100 to achieve several abilities such asany one or more of the following: (a) speeding object detection andscans of the FOV by potentially eliminating a need to search for objectsusing increasing amounts of light, (b) reduce the overall energy usedfor detection across the FOV, (c) allow diversion of energy allotment toregions where it can be of greater impact, (d) reduce the environmentaleffect of the LIDAR system, e.g. by reducing excessive light emission indirection where objects are known to be present, and (e) reducingprocessing requirements for processing superfluous detected signals.

FIG. 13 provides a flow chart representation of a method 1302 fordetecting objects using a LIDAR system. During operation of LIDAR system100 in a manner consistent with the presently disclosed embodiments, anyor all steps may include controlling at least one light source in amanner enabling light flux to vary over a scan of a field of view usinglight from the at least one light source. Any or all operational stepsmay also include controlling at least one light deflector to deflectlight from the at least one light source in order to scan the field ofview. At step 1308, method 1302 may include using first detectedreflections associated with a scan of a first portion of the field ofview to determine an existence of a first object in the first portion ata first distance. At step 1310, method 1302 may include determining anabsence of objects in a second portion of the field of view at the firstdistance. At step 1312, method 1302 may include altering a light sourceparameter such that more light is projected toward the second portion ofthe field of view than is projected toward the first portion of thefield of view following the detection of the first reflections and thedetermination of the absence of objects in the second portion. At step1314, method 1302 may include using second detected reflections in thesecond portion of the field of view determine an existence of a secondobject at a second distance greater than the first distance. It shouldbe noted that an increase in light flux in order to detect the secondobject in the second portion may be made during a current scan of theFOV or during a subsequent scan of the FOV. Optionally, if stages 1310,1312 and 1314 are executed after the detection of stage 1308, all of theemissions toward the second FOV portion used in the detection of thesecond object are emitted before additional light is emitted to thefirst portion (e.g. at a later scan cycle).

In some embodiments, the method may include scanning of FOV 120 over aplurality of scanning cycles, wherein a single scanning cycle includesmoving the at least one light deflector across a plurality ofinstantaneous positions. While the at least one light deflector islocated at a particular instantaneous position, the method may includedeflecting a light beam from the at least one light source toward anobject in the field of view, and deflecting received reflections fromthe object toward at least one sensor.

Incremental Flux Allocation for Lidar Detection

As described above, light flux may be varied to a second region of theLIDAR FOV when no objects are detected in that region at a firstdistance D1, where one or more objects were detected in a differentregion of the LIDAR FOV. Additionally, however, in some embodimentslight flux may be varied to a particular region of the LIDAR FOV basedon whether objects are detected in that region at any distance. Forexample, based on a first amount of light provided to a particularregion of a LIDAR FOV, processor 118 may make a determination that noobjects reside in that region within a distance S1 from the LIDAR system100. In response to such a determination, processor 118 may cause morelight to be provided to the particular portion of the FOV. With theincrease in light, processor 118 may make a determination that noobjects reside in the particular region within a distance S2 from theLIDAR system 100, where S2>S1. In response to such a determination, evenmore light may be provided to the particular region of the LIDAR FOV,and in response to this increase in light, processor 118 may detect thepresence of one or more objects at a distance S3 from the LIDAR system100, where S3>S2>S1. Thus, such increases in light provided to aparticular region of the LIDAR FOV may enhance the detectioncapabilities of the LIDAR system within the particular region.Furthermore, using the disclosed gradual illumination scheme allows toachieve detection at long range at a limited power consumption.

FIG. 14 provides a diagrammatic illustration of a LIDAR field of view1410 and an associated depth map scene representation that may begenerated by LIDAR system 100. As shown, at distances within a range.S0, relatively close to LIDAR system 100 (the point of view in FIG. 14),objects in the scene may be detected. Range S0 may cover varyingdistance intervals depending on the operational parameters of LIDARsystem 100. In some cases, S0 may represent a range of between 0 m and10 m. In other cases, S0 may correspond to a range of 0 m to 20 m, 30 m,50 m, etc.

In some instances, LIDAR system may determine an absence of detectedobjects in a first portion of the field of view at a first distance, S1.For example, as shown in FIG. 14, based on light projected to aparticular region 1412 of LIDAR FOV 1410 (e.g., a first light emission),LIDAR system may identify various foreground objects, such as a surfaceof a road 1414, a curb 1416, and/or a surface of a sidewalk 1418.Processor 118 of LIDAR system 100, however, may not detect any objectsin region 1412 at a distance S1. That is, processor 118 may make adetermination that there is an absence of objects in region 1412 atdistance S1 (and possibly beyond). In some embodiments, distance S1 maybe greater than distance S0. For example, S0 may include a range ofbetween 0 m up to distance S1 at 20 m. In some examples, S1 may be equalto distance S0 and/or smaller than distance S0. For example, if thefirst light emission in the relevant scenario (e.g. ambient lightconditions) would allow detection of given-reflectivity objects of up toabout 40 meters from the LIDAR system, the first light emission mayallow the system to determine absence of objects of at least suchreflectivity in distances 20 m, 30 m, 39 m, and possibly even 40 m.

There may be several reasons that LIDAR system 100 does not detectobjects at distance S1 in region 1412. For example, in some cases, theremay not be any objects present in that region at distance S1. In othercases, however, the amount of light projected to region 1412 may beinsufficient to detect objects at distance S1, whether because thoseobjects are characterized by low reflectance or whether distance S1 isbeyond the operational range of LIDAR system 100 for a particular set ofoperational parameters (e.g., duration, intensity, power level, etc. oflight projected to region 1412).

Rather than giving up on detection of objects at distance S1 in region1412 when no objects are detected there based on a first light emission,processor 118 may cause additional light flux to be supplied to region1412 in order to detect, if possible, objects at distances beyond S1. Inother words, when processor 118 determines an absence of objectsdetected in the first portion 1412 of the field of view 1410 based onthe first light emission, processor 118 may control projection of atleast a second light emission directed toward region 1412 of the fieldof view 1410 to enable detection of an object in region 1412 at a seconddistance. S2, greater than the first distance, S1. Not only may thesecond emission potentially increase a capability for detecting objectsat distance S2, but the second emission may also increase the potentialfor LIDAR system 100 detecting objects at distance S1.

In some cases, processor 118 may cause light projector 112 and deflector114 to project additional light toward region 1412. For example,processor 118 may control projection of at least a third light emissiondirected toward region 1412 of the field of view 1410 to determine anexistence of an object in region 1412 at a third distance S3 greaterthan the second distance S2, which is greater than distance S1. As shownin FIG. 15, a third light emission to region 1412 may enable detectionof a pedestrian 1510 (or at least a part thereof) at distance S3 fromLIDAR system 100. While pedestrian 1510 may not have been detected inresponse to the first or second light emissions directed toward region1412, the third emission to region 1412 enabled determination of thepresence of pedestrian 1510 at distance S3. Moreover, the second andthird light emissions enabling detection of objects in region 1412 at asecond distance, S2, or at a third distance, S3, respectively, may haveenabled LIDAR system 100 to detect objects (e.g., curb 1416, roadsurface 1414, and/or sidewalk 1418) beyond a distance range S0. Forexample, as shown in FIG. 15, such objects have been detected and mappedfor distances up to and beyond distance S3.

Thus, as described above, processor 118 may cause additional lightemissions to be projected toward a particular region of the LIDAR FOVbased on whether objects are detected in that region at variousdistances. For example, in one embodiment processor 118 may beconfigured to control projection of at least a third light emissiondirected toward a particular portion/region of the LIDAR FOV when, basedon detection of at least one of a first light emission and a secondlight emission, the absence of objects is determined in the portion ofthe LIDAR FOV at a first distance (e.g., S1 in FIG. 14). Additionally,processor 118 may be configured to control projection of at least athird light emission toward a particular region/portion of the LIDAR FOVwhen, based on detection of at least a second light emission, theabsence of objects is determined in that portion of the LIDAR FOV at ssecond distance (e.g., distance S2 in FIG. 14).

Distances S1, S2, and S3 may depend on the particular operationalparameters of LIDAR system 100, which may be selected to suit aparticular deployment of LIDAR system 100 (e.g., on a vehicle, building,aircraft, etc.), to suit particular weather conditions (e.g., clearweather, rain, snow), or to suit any other environmental conditions(e.g., rural vs. urban environments, etc.). In some embodiments,however, distance S1 may be 20 m or less from LIDAR system 100. DistanceS3 may include distances greater than 100 m, and distance S2 may fallbetween distance S1 and S3. As discussed in greater detail with respectto the notion of detection distances of the LIDAR system, it is notedthat the aforementioned detection distances (S0, S1, S2, S3) are notnecessarily defined in advance, and that these distances may be adetermined based on light emission energy schemes used by the LIDARsystem. Furthermore, the detection distances may also depend on otherfactors such as weather, ambient light conditions, visibility, targetsreflectivity, and so on. It is further noted that in FIGS. 14 and 15,the detection range S0 has been illustrated, for the sake of simplicity,as uniformly extending from a vertical plane on which the LIDAR systemis located. However, as noted, any of the detection ranges are notnecessarily uniform across different portions of the FOV, and thedistances may be measured radially from a point located on an opticalwindow of the LIDAR, rather than from a zero-distance plane (asillustrated).

Here and relative to any of the disclosed embodiments, a particularportion or region of the LIDAR FOV may refer in some embodiments to asingle pixel of the scan of the FOV. In those embodiments, theparticular portion of the FOV may correspond to a single instantaneousposition of deflector 114 as it is moved through a range ofpositions/orientations in order to scan the LIDAR FOV. With reference toFIG. 14, for example, region 1412 (e.g., a portion of the LIDAR FOV) mayrepresent a single pixel of LIDAR FOV 1410. In other embodiments,however, a particular region of the LIDAR FOV may include multiplepixels. For example, a region 1520 of the LIDAR FOV may include multiplepixels each corresponding to a different instantaneous position ofdeflector 114. The individual pixels included in a region or portion ofthe FOV may be contiguous, such as the pixels included in region 1520,or they may be discontinuous. In some cases, a portion of the FOV mayrepresent a particular region of interest within the LIDAR FOV, may besubjected to similar light emission protocols, etc.

In some embodiments, the relative position of a particular portion ofthe LIDAR FOV within the LIDAR FOV may vary. For example, in some cases,deflector 114 may be continuously moved (e.g. in a sweeping pattern, ina raster pattern, randomly, pseudo-randomly) through a plurality ofinstantaneous positions, each corresponding to a particular region ofthe LIDAR FOV. In the process described above, there may exist someamount of time between the first light emission to a particular portionof the FOV and the second light emission to the same portion of the FOV.During that time, deflector 114 may move such that the exactinstantaneous position of the deflector during the first emission may bedifferent from its exact instantaneous position during the secondemission. Similarly, an exact instantaneous position of deflector 114during the third emission may be different from its exact instantaneouspositions during the first and second emissions. As a result the regionsof the LIDAR FOV illuminated by the first, second, and third emissionsmay differ slightly with respect to one another. For purposes of thisdisclosure, however, grouped light emissions or light emissionsprojected toward substantially overlapping regions of the LIDAR FOV willbe considered as directed to the same region of the LIDAR FOV. In otherwords, in some embodiments, a particular portion of the LIDAR FOV maycorrespond to a single instantaneous position of deflector 114. In otherembodiments, a particular portion of the LIDAR FOV may correspond to twoor more instantaneous positions of deflector 114.

As noted above, by monitoring and/or processing the output of one ormore sensors, such as sensor 116, processor 118 may determine both thepresence of objects within a particular region of the LIDAR FOV or theabsence of objects within the same region. For example, as shown in FIG.14 reflections of light projected to FOV region 1412 may enabledetection and depth mapping of objects such as road surface 1414, curb1416, or sidewalk 1418, especially at distances within the S0 range. Onthe other hand, the same projection of light to region 1412 may notresult in detection or depth mapping ability for objects at a distanceS1 or at a further distance S2 from the LIDAR system. In such cases,based on the information obtained from the available reflections oflight from region 1412, processor 118 may make a determination thatthere is an absence of objects in region 1412 at distances beyond S0,S1, S2, etc.

A determination of an absence of objects may not mean there are actuallyno objects present in a particular region of the LIDAR FOV. Rather, asdescribed above, such a determination may be made when detector 116receives insufficient light reflections from a particular region todetect an object in that region. A determination of an absence of anobject may also be made, for example, if reflections are collected, butinsufficient information exists from which to determine ranginginformation to the at least one source of the reflections or to generatea depth map based on the received reflection(s). Increasing light fluxlevels to a particular region of the FOV, as described with respect toFIGS. 14 and 15, however, may result in the detection of objects thatpreviously went undetected. And object detection may not involve abinary process (e.g., either a reflection from an object is received orno reflections are received). Rather, detection may require thatdetector 116 receives sufficient light reflections for processor 118 torecognize the presence of an object in a particular region where lightwas projected. Thus, whether detection occurs or not may depend onvarious factors, such as object reflectivity, distance to an object,etc. As described herein, light projections that are described asenabling detection at one distance or another may constitute lightprojections that result in positive detections in a certain percentageof instances (e.g., at least in 50%, 75%, 90%, 99% or more of instancesinvolving light projections of a certain set of characteristics)involving objects having a certain level of reflectivity (e.g.,reflectivity levels of at least 2.5%, 5%, 10%, etc.).

Using the process described above for increasing light flux to aparticular region of the LIDAR FOV based on whether objects are detectedin that region at various distances, a scan of a LIDAR FOV may beperformed in which multiple objects may be detected using lightprojections from anywhere within a light projection sequence associatedwith a particular FOV region. For example, in some instances objects maybe detected in one region of a LIDAR FOV using only a first lightemission. Scanning of other portions of the LIDAR FOV may result inobjects being detected in those regions only after a second lightemission, a third light emission, etc. is provided to those regions. Inthe exemplary embodiment represented by FIGS. 14 and 15, a first lightemission to FOV region 1530 may result in detection of a surface of road1414. In region 1412, a first light emission may result in the detectionof objects such as sidewalk 1418, curb 1416, and road 1414 at least upto a certain range (S0 or S1, as shown in FIG. 14). A subsequent (e.g.,second) light emission directed toward region 1412 may result indetection of sidewalk 1418, curb 1416, and road 1414 at a longer range(e.g., S2). A third light emission directed toward region 1412 mayresult in detection of a pedestrian 1510 at distance S3. Similar resultsmay be obtained for one or more other regions in FOV 1410. Of course,some regions may receive only one light emission (or even no lightemission at all), while other regions may receive multiple lightemissions. As a result, a particular scan of the LIDAR FOV may includeobjects detected based on first light emissions, second light emissions,and/or third light emissions, etc. depending on how many light emissionswere projected toward a particular region.

There are various techniques that may be used to increase light flux toa particular region of the LIDAR FOV, including any described above orbelow. In some instances, in order to vary light flux to a particularregion of the FOV, processor 118 may control light projector 112 (e.g.,its aiming direction, power level, light intensity, wavelength, pulsewidth, duration of continuous wave application, etc.). In other cases,processor 118 may control the at least one light deflector 114 in orderto vary light flux (e.g., by controlling an orientation and therefore adirection of projection toward a particular region of the FOV,controlling an amount of time light is projected to a certain region ofthe FOV etc.).

Further, processor 118 may control at least one aspect of both the lightprojector 112 and at least one aspect of the deflector 114 in order tocontrol an amount of light received by a particular region of the FOV.For example, in some embodiments, processor 118 may control lightprojector 112 to emit multiple emissions of light energy. Processor 118may also control light deflector 114 such that a first light emission, asecond light emission, and a third light emission provided by the lightprojector 112 are all projected toward a particular portion of the LIDARFOV that corresponds with a single instantaneous position of lightdeflector 114 (or at least closely spaced instantaneous positions of thedeflector). Each of the first, second, and third light emissions mayhave similar characteristics (e.g., power level, duration, number ofpulses, wavelength, etc.). Alternatively, one or more of the first,second, and third light emissions may have different characteristics.For example, one or more of the emissions may exhibit a higher powerlevel than the others. In some embodiments, a power level associatedwith the first, second, and third light emissions may progressivelyincrease with each emission. And in some embodiments, processor 118 maybe configured to control the light projector 112 (which may include amulti-wavelength source or multiple sources each capable of emittinglight at a different wavelength) such a first light emission projectedtoward a particular region of the FOV has a wavelength different fromboth a second light emission and a third light emission directed towardthe particular region of the FOV. In some examples, each one of thefirst light emission, second light emission and third light emissionincludes a single pulse (optionally, these pulses may be of similarcharacteristics). In some examples, each one of the first lightemission, second light emission and third light emission includes thesame number of pulses (optionally, these pulses may be of similarcharacteristics). In some examples, each one of the first lightemission, second light emission and third light emission includes one ormore pulses (optionally, these pulses may be of similarcharacteristics).

In some embodiments, each of the light emissions projected toward aparticular region of the LIDAR FOV may have a similar light intensity(e.g., substantially the same light intensity). In other embodiments,however, processor 118 may cause the light intensity of the variouslight emissions from light projector 112 to vary. For example, processor118 may be configured to control light projector 112 such that a secondlight emission has a light intensity greater than a light intensity of afirst light emission provided by light projector 112 relative to aparticular region of the FOV. Similarly, processor 118 may control lightprojector 112 such that a third light emission from light projector 112relative to a particular region of the FOV has a light intensity greaterthan a light intensity of the second light emission.

Similarly, each of the light emissions projected toward a particularregion of the LIDAR FOV may have a similar power level. In otherembodiments, however, processor 118 may cause the light power level ofthe various light emissions from light projector 112 to vary. Forexample, processor 118 may be configured to control light projector 112such that a second light emission has a power level greater than a powerlevel of a first light emission provided by light projector 112 relativeto a particular region of the FOV. Similarly, processor 118 may controllight projector 112 such that a third light emission from lightprojector 112 relative to a particular region of the FOV has a powerlevel greater than a power level of the second light emission. In stillother cases, a power level associated with one or more light emissionsfollowing a first light emission to a particular region of the LIDAR FOVmay be lower than a power level associated with the first lightemission. As a result of additional light emissions provided to aparticular region of the LIDAR FOV, the accumulated light energy mayincrease with each subsequent emission, which may increase the chancesof object detection in that area, including at progressively longerdistances.

In view of the cumulative effect of light energy provided to aparticular portion of the LIDAR FOV, different light emissions or pulsesmay be used together with one another to detect objects in that portionof the FOV. For example, in some embodiments, processor 118 may use athird light emission projected toward a particular region of the FOValong with either or both of a first light emission or a second lightemission projected toward that region in order to determine theexistence of an object in that portion of the FOV. Further, thecumulative light energy may enable an increased detection distance. Byusing both the first emission and either or both of the second or thirdemissions, processor 118 may be enabled to detect an object at adistance (e.g., S3) that is larger than a detection distance associatedwith either the second emission alone (e.g., S2) or the first emissionalone (e.g., S0).

In addition to using multiple light emissions to detect an object, themultiple light emissions may also be used in creating data points foruse in generating a depth map representative of objects in a scene. Forexample, in some embodiments a data point for a depth map may be createdbased solely on a first light emission projected toward a particularregion of the LIDAR FOV. In other embodiments, data points for a depthmap may be created based on a combination of the first emission and asecond emission and/or a third emission (or more) projected toward theparticular region of the FOV.

Moreover, a particular object may be detected at different times (e.g.,in different scans of the LIDAR FOV) using different combinations oflight emissions. In some cases, at time T0, multiple light emissions maybe required in combination (e.g., two, three, or more emissions) todetect the presence of pedestrian 1510 (FIG. 15). As the distance topedestrian 1510 decreases (e.g., as a vehicle on which LIDAR system 100is deployed approaches pedestrian 1510), fewer light emissions may berequired to detect pedestrian 1510. For example, when a distance topedestrian 1510 is less than S0, pedestrian 1510 may be detected duringa subsequent FOV scan based on a single light emission to a particularregion of the LIDAR FOV.

In the described embodiments for dynamically varying an amount of lightflux provided to particular regions of the LIDAR FOV during scans of theFOV, more light may be projected to a particular region of the FOV thanis projected to one or more other regions of the LIDAR FOV during a scanof the FOV. For example, processor 118 may be configured to alter alight source parameter associated with light projected to a firstportion of the LIDAR FOV such that during a same scanning cycle of theFOV, light flux of light directed to the first portion is greater thanlight flux of light directed to at least one other portion of the LIDARFOV. Processor 118 may also monitor amounts of light provided to variousregions of the FOV to ensure compliance with applicable regulations. Forexample, processor 118 may be configured to control light projector 112such that an accumulated energy density of the light projected to anyparticular portion of the LIDAR FOV does not exceed a maximumpermissible exposure limit (either within any single scan of the FOV orover multiple scans of the FOV).

For example, processing unit 108 may control gradual projection of lightonto a portion of the LIDAR FOV, intermittently determining when anobject is detected in the respective portion of the LIDAR FOV, and whenan object is detected processing unit 108 control the light emission tothat portion of the FOV to remain within a safe light emission limit,which would not cause harm to the detected object. These techniques maybe implemented in a complimentary fashion: in each of one or moreportions of the FOV, processing unit 108 may implement together astopping condition (preventing excision of a maximum permissibleexposure limit) while continuously checking in a complimentary fashionwhether additional light is needed (e.g. by determining that the lightprojected so far toward the portion of the LIDAR FOV is insufficient fora valid detection of an object).

It is noted that LIDAR system 100 may include preliminary signalprocessor (not illustrated) for processing the reflections signals of anearly light emission (e.g., the first light emission, the second lightemission) in a fast manner, in order to allow quick decision regardingfollowing emission of light (e.g., the second light emission, the thirdlight emission)—especially if the following emission of light is to beexecuted within the same scanning cycle, and particularly if thefollowing emission of light is to be executed while the light deflectoris still in substantially the same instantaneous position. The quickdecision regarding the following emission may include a decision whetherany further emission is required (e.g., the second emission, the thirdemission), and may also include determination of parameters for thesubsequent emission for each segment. It is noted that some or all ofthe circuitry of preliminary signal processor may be different than thecircuitry of the range estimation module which is used to determineranges of points in the 3D model. This is because the quick decisiondoes not necessarily need an exact range estimation (for example, just adetermination of a presence or absence of object may suffice). Anotherreason for using different circuitry is that the main range estimationcircuitry may not be fast enough to make decision in the rate requiredfor emitting further light emissions in the same instantaneous positionof the at least one light deflector. It is noted that the processingresults of such a preliminary signal processor may possibly beinsufficient for range estimation. Optionally, the preliminary signalprocessor may be an analog processor which processes analog detectionsignals (e.g. voltages), while the main range estimator module may be(or include) a digital processing module, which process thedetection-information after it have been converted from analog todigital. It is further noted that the same (or a similar) preliminarysignal processing module may be implemented in LIDAR system 100, andused for detection of objects in an immediate area of the LIDAR system,to prevent emission of excessive light energy (e.g. for reasons of eyesafety), as discussed below in greater detail.

Increases in light flux provided to a particular portion of the LIDARFOV may proceed according to any suitable protocol. For example, in someembodiments, as described above, first, second, and third lightemissions (or more or fewer emissions) may be projected to a particularregion of the LIDAR FOV before deflector 114 is moved to a differentinstantaneous position for scanning a different region of the FOV. Inother words, processor 118 may be configured to control deflector 114such that a first light emission, a second light emission, and a thirdlight emission are projected toward a particular portion of the LIDARFOV in a single scanning cycle.

In other cases, multiple light emissions designated for a particularregion of the LIDAR FOV may be projected toward that portion of the FOVduring different scans of the FOV. For example, processor 118 may beconfigured to control deflector 114 such that one or more of a firstlight emission, a second light emission, and a third light emission areeach projected toward a particular portion of the LIDAR FOV in differentscanning cycles.

Disclosed embodiments may be used to perform a method for detectingobjects using a LIDAR system. For example, as described above, detectingobjects with LIDAR system 100 may include controlling at least one lightsource in a manner enabling light flux to vary over a scan of a LIDARfield of view using light from the at least one light source. As shownin FIG. 16, a method for detecting objects with LIDAR system 100 mayalso include controlling projection of at least a first light emissiondirected toward a first portion of the field of view (step 1620) todetermine an absence of objects in the first portion of the field ofview at a first distance (step 1630). The method may also includecontrolling projection of at least a second light emission directedtoward the first portion of the field of view to enable detection of anobject in the first portion of the field of view at a second distance,greater than the first distance, when an absence of objects isdetermined in the first portion of the field of view based on the atleast a first light emission (step 1640). And the method may includecontrolling projection of at least a third light emission directedtoward the first portion of the field of view to determine an existenceof an object in the first portion of the field of view at a thirddistance, greater than the second distance (step 1650).

Adaptive Noise Mitigation for Different Parts of the Field of View

In a LIDAR system consistent with embodiments of the present disclosure,the captured signals may include noise. Noise may result from a varietyof sources. For example, some noise may arise from the detector (e.g.,sensing unit 106 of FIGS. 4A-4C) and may include dark noise,amplification noise, etc. In addition, some noise may arise from theenvironment and may include ambient light or the like. For example,ambient noise may be strong with respect to the reflection signal if theLIDAR system projects light into the sky, toward objects very far away,or toward other areas where reflection is minimal. On the other hand,ambient noise may be lower with respect to the reflection signal if theLIDAR system projects light onto object positioned in dark areas of afield of view. In one example, ambient light may comprise light arrivingto the LIDAR system directly from an external source of light (e.g. thesun, headlights of a car, electric lighting apparatus). By way offurther example, ambient light may comprise light from an externalsource of light arriving to the LIDAR system after being deflected(e.g., reflected) by an object in the FOV (e.g., reflections of thelight from metallic or non-metallic surfaces, deflections by atmosphere,glass or other transparent or semitransparent objects, or the like).

Systems and methods of the present disclosure may collect data on apixel-by-pixel basis (e.g., relative to sensing unit 106). Additionally,a LIDAR system consistent with embodiments of the present disclosure mayaddress noise resulting from various sources and may do so also on apixel-by-pixel basis.

As used herein, the term “pixel” is used broadly to include a portion ofthe FOV of the LIDAR system which is processed to an element of aresulting model of objects in the FOV. For example, if the detectiondata of the sensor is processed to provide a point cloud model, a“pixel” of the FOV may correspond to a portion of the FOV which istranslated into a single data point of the point cloud model. In oneexample, the dimensions of a pixel may be given using a solid angle, ortwo angles of its angular size (e.g., ϕ and θ). In some embodiments, asingle “pixel” of the FOV may be detected by a plurality of sensors(e.g., multiple SiPM detectors) to provide a corresponding plurality ofdata points of the 3D model. In a scanning system, a pixel of the FOVmay be substantially of the same angular size as the beam of laserprojected onto the scene or may be smaller than the angular size of thebeam (e.g., if the same beam covers several pixels). A pixel being thesame size of the laser beam spot means that most of the photons of thelaser beam (e.g., over 50%, over 70%, over 90%, etc.) emitted within thepart of the FOV are defined as the respective pixel. In someembodiments, any two pixels of the FOV may be completely nonoverlapping.However, optionally, some pairs of pixels may partly overlap each other.

Systems and methods of the present disclosure may allow for noiseestimation, mitigation, and possibly cancellation, for example, byaltering the sensitivity of the detector (e.g., sensing unit 106 ofFIGS. 4A-4C). FIG. 17 illustrates an example method 1700 for alteringsensor sensitivity in a LIDAR system. Method 1700 may be performed by atleast one processor (e.g., processor 118 of processing unit 108 of LIDARsystem 100 as depicted in FIG. 1A and/or two processors 118 ofprocessing unit 108 of the LIDAR system depicted in FIG. 2A).

At step 1701, processor 118 controls at least one light source (e.g.,light source 112 of FIG. 1A, laser diode 202 of light source 112 of FIG.2A, and/or plurality of light sources 102 of FIG. 2B) in a mannerenabling light flux to vary over a scan of a field of view (e.g., fieldof view 120 of FIGS. 1A and 2A). For example, processor 118 may vary thetiming of pulses from the at least one light source. Alternatively orconcurrently, processor 118 may vary the length of pulses from the atleast one light source. By way of further example, processor 118 mayalternatively or concurrently vary a size (e.g., length or width orotherwise alter a cross-sectional area) of pulses from the at least onelight source. In a yet further example, processor 118 may alternativelyor concurrently vary the amplitude and/or frequency of pulses from theat least one light source. In yet another example, processor 118 maychange parameters of a continuous wave (CW) or quasi-CW light emission(e.g., its amplitude, its modulation, its phase, or the like).

In some embodiments, the field of view (e.g., field of view 120 of FIGS.1A and 2A) may include at least a first portion and a second portion.For example, the first portion and the second portion may comprisehalves, fourths, or other fractions of the area covered by the field ofview. In other examples, the first portion and the second may portionmay comprise irregular, rather than symmetric and/or fractional,portions of the area covered by the field of view. In still otherexamples, the first portion and the second may portion may comprisediscontinuous portions of the area covered by the field of view. In someexamples, the first portion of the FOV may be one FOV pixel, and thesecond portion of the FOV may be another pixel. In yet other examples,the first portion of the FOV may include a number of FOV pixels, and thesecond portion of the FOV may include a different group of the samenumber of pixels. In some embodiments, the first portion and the secondportion of the FOV may be partly overlapping. Alternatively, the firstportion and the second portion may be completely nonoverlapping.

Step 1701 may further include controlling at least one light deflector(e.g., light deflector 114 of FIG. 1A, deflector 114A and/or deflector114B of FIG. 2A, and/or one-way deflector 214 of FIG. 2B) in order toscan the field of view. For example, processor 118 may cause mechanicalmovement of the at least one light deflector to scan the field of view.Alternatively or concurrently, processor 118 may induce a piezoelectricor thermoelectrical change in the at least one deflector to scan thefield of view.

In some embodiments, a single scanning cycle of the field of view mayinclude moving the at least one deflector such that, during the scanningcycle, the at least one light deflector is located in a plurality ofdifferent instantaneous positions (e.g., the deflector is controlledsuch that the deflector moves from or through one instantaneous positionto another during the scan of the LIDAR FOV). For example, the at leastone light deflector may be moved continuously or non-continuously fromone of the plurality of positions to another (optionally with additionalpositions and/or repetitions) during the scanning cycle.

In such embodiments, processor 118 may coordinate the at least one lightdeflector and the at least one light source such that, when the at leastone light deflector is located at a particular instantaneous position, alight beam is deflected by the at least one light deflector from the atleast one light source towards the field of view and reflections from anobject in the field of view are deflected by the at least one lightdeflector toward at least one sensor. Accordingly, the at least onelight deflector may direct a light beam toward the field of view andalso receive a reflection from the field of view. For example, FIGS. 1A,2B, and 2C depict examples in which a deflector both directs a lightbeam towards the field of view and also receives a reflection from thefield of view. In certain aspects, the reflection may be caused by thelight beam directed toward the field of view. In other embodiments, alight beam from the at least one light source may be directed towardsthe field of view by at least one light deflector separate from at leastone other light deflector that receives a reflection from the field ofview. For example, FIG. 2A depicts an example in which one deflectordirects a light beam towards the field of view and a separate deflectorreceives a reflection from the field of view.

At step 1703, processor 118 receives, on a pixel-by-pixel basis, signalsfrom at least one sensor (e.g., sensing unit 106 of FIGS. 4A-4C). Forexample, the signals may be indicative of at least one of ambient lightand light from the at least one light source reflected by an object inthe field of view. As explained above, in certain aspects, for example,aspects in which the object is dark and/or far away, the ambient lightmay account for a greater portion of the signal than the reflectedlight. In other aspects, for example, aspects in which the object isbright and/or close by, the ambient light may account for a smallerportion of the signal than the reflected light.

The received signals may further be indicative of at least one ofambient light and light from the at least one light source reflected byan object in the field of view combined with noise associated with theat least one sensor. For example, dark noise, amplification noise,and/or the like may be combined in the signals with ambient light and/orreflected light. In particular, the signals from at least one sensor mayinclude noise that originates from amplification electronics.

The received signals may be associated with various portions of thefield of view. For example, at least one signal may be associated with afirst portion of the field of view while at least one other signal maybe associated with a second portion of the field of view. In someembodiments, each signal may be associated with a particular portion ofthe field of view. In other embodiments, some and/or all signals may beassociated with multiple portions of the field of view (e.g., inembodiments where portions of the field of view have overlappingsections).

In some embodiments, step 1703 may further include receiving signals fordifferent pixels in different times. For example, if the at least onedeflector is moved during a scanning cycle, as discussed above,processor 118 may receive signals corresponding to different pixels atdiffering times that depend on when the at least one deflector is in aparticular instantaneous location.

At step 1705, processor 118 estimates noise in at least one of thesignals associated with the first portion of the field of view.Processor 118 may use a variety of noise estimation techniques, eitherindividually or in combination, to estimate noise in the at least onesignal. Examples of noise estimation techniques are discussed below withreferences to FIGS. 18 and 19.

In some embodiments, processor 118 may estimate the noise in eachportion of the field of view based on reflections associated with asingle position of the at least one light deflector (each portion may beless than 10%, 5%, 1%, 0.1% etc. of the field of view). For example,processor 118 may extrapolate the estimated noise from the singleposition to other positions in the same portion. In some embodiments,the extrapolation may comprise copying the estimated noise from thesingle positions to other positions.

In other embodiments, the extrapolation may comprise applying one ormore functions to the estimated noise from the single positions togenerate outputs of estimated noise for other positions. For example,the function may depend on the distance between the other positions andthe single position, a difference between an actual and/or predictedbrightness of the other positions and of the single position, adifference between a previously estimated noise in the other positionsand the currently estimated noise in the single position, or the like.The function may output estimates for the other positions directly, mayoutput adjustment factors (e.g., for adding, subtracting, multiplying,or the like) for transforming the estimated noise for the singleposition to estimates for the other positions, or may be convolved withor otherwise operate on the estimated noise for the single position toproduce estimates for the other positions or adjustment factors.Likewise, in some examples, processor 118 may estimate the noise for asingle position based on noise estimates (or on the original signals) ofa plurality of other portions of the FOV, e.g., by averaging the noiseestimates from locations surrounding the FOV portion.

In some embodiments, each portion may comprise less than 10% of thefield of view. In certain aspects, each portion may comprise less than5% of the field of view. For example, each portion may comprise lessthan 1% of the field of view. By way of further example, each portionmay comprise less than 0.1% of the field of view.

Alternatively or concurrently, processor 118 may estimate a noise insignals associated with a particular portion of the field of view basedon a comparison of signals associated with the particular portion of thefield of view received in at least one previous scanning cycle. Forexample, processor 118 may apply one or more functions to at least oneprevious signal to generate outputs of estimated noise for otherpositions. For example, the function may depend on the time between theprevious signals and the current signals, a difference between an actualand/or predicted brightness of the previous signals and of the currentsignals, the previously estimated noise in the previous signals, or thelike. The function may output noise estimates for the current signalsdirectly, may output adjustment factors (e.g., for adding, subtracting,multiplying, or the like) for transforming the estimated noise for theprevious signals to estimates for the current signals, or may beconvolved with or otherwise operate on the estimated noise for theprevious signals to produce estimates for the current signals oradjustment factors.

At step 1707, processor 118 may alter a sensor sensitivity forreflections associated with the first portion of the field of view basedon the estimation of noise in the first portion of the field of view.For example, sensor sensitivity may be based on a signal-threshold. Insome embodiments, processor 118 may increase the signal-threshold forthe first portion relative to the signal-threshold for the secondportion. Processor 118 may do so, for example, when the noise estimationin the first portion is higher than the noise estimation in the secondportion. Accordingly, the higher signal-threshold in the first portionthe more of the estimated noise that may be filtered out.

In some embodiments, the sensor sensitivity may be altered in thedetector(s) of the sensor. Alternatively or concurrently, the sensorsensitivity may be altered in processor 118. For example, thesignal-threshold may be altered with respect to the pre-processed dataor the post-processed data. In one example, the sensor may output analogdata, which may be converted to a digital sampling (e.g., amplitude intime, or the like). After correlating (e.g., convoluting, or the like)the digital sampling to a function representing an expected signal (asdescribed below with respect to FIG. 18), the signal-threshold may beapplied to the output of the correlation.

In some embodiments, processor 118 may alter a sensor sensitivity forreflections associated with a portion of the FOV by altering anoperational parameter of processor 118. The alteration of theoperational parameter in such cases may modify the sensor sensitivity bychanging the sensitivity of the detection to the signal level and/ornoise level acquired by the at least one sensor. For example, processor118 may alter the sensor sensitivity (e.g., in steps 1707 and/or 17011)by changing a post-convolution threshold, as discussed in the previousparagraph. However, other operational parameters of processor 118 mayadditionally or alternatively be altered by processor 118 in response tothe noise levels in order to alter the sensor sensitivity.

By way of additional example, processor 118 may estimate a level ofnoise on account of dark noise and/or amplification noise and alter asensor sensitivity such that the sensitivity has a minimum thresholdhigher than the estimated level of noise. Accordingly, the estimatednoise may be minimized, if not cancelled or eliminated, by setting theminimum threshold accordingly.

In some embodiments, processor 118 may alter a sensor sensitivity forreflections associated with a portion (e.g., the first portion) of thefield of view corresponding to a single instantaneous position of the atleast one light deflector. For example, processor 118 may alter thesensor sensitivity only during times at which the at least one lightdeflector is in a particular instantaneous position. In otherembodiments, processor 118 may alter a sensor sensitivity forreflections associated with a portion (e.g., the first portion) of thefield of view corresponding to a plurality of instantaneous positions ofthe at least one light deflector. For example, processor 118 may alterthe sensor sensitivity for varying times at which the at least one lightdeflector is in different positions from among the plurality ofinstantaneous positions. In certain aspects, the altered sensitivity forthe plurality of instantaneous positions may be equivalent—that is,processor 118 may, during times at which the at least one lightdeflector is in one of the plurality of instantaneous positions, alterthe sensor sensitivity in the same manner. In other aspects, the alteredsensitivity may be different for the plurality of instantaneouspositions—that is, processor 118 may, during times at which the at leastone light deflector is in one of the plurality of instantaneouspositions, alter the sensor sensitivity in a manner different from whenthe at least one light deflector is in another of the plurality ofinstantaneous positions.

Alternatively or concurrently, step 1707 may further includeindividually altering the sensor sensitivity for reflections associatedwith the first and second portions such that, for a same amount of lightprojected toward the first portion and the second portion, a detectiondistance associated with the first portion is higher than a detectiondistance associated with the second portion (e.g., by a factor of atleast 50%). Accordingly, the sensor sensitivity of the first portion maybe increased (and/or a minimum threshold decreased and/or a maximumthreshold increased) to increase the detection distance.

Alternatively or concurrently, step 1707 may further includeindividually altering the sensor sensitivity for reflections associatedwith the first and second portions such that, for a same amount of lightprojected toward the first portion and the second portion, a resolutionassociated with the first portion is higher than a resolution associatedwith the second portion. Accordingly, the sensor sensitivity of thefirst portion may be increased (and/or a minimum threshold decreasedand/or a maximum threshold increased) to increase the resolution.

In some embodiments, step 1707 may be performed only after step 1705 isfinalized. Furthermore, in some embodiments, the alteration of sensorsensitivity for a portion of the FOV (e.g., steps 1707 and 1711) may beperformed after the corresponding noise estimation for the respectivepart of the FOV on which the alteration is based (e.g., steps 1705 and1709, respectively) without any measurement for any other part of theFOV. Similarly, in some embodiments, the alteration of sensorsensitivity for a portion of the FOV (e.g., steps 1707 and 1711) may beperformed after the corresponding noise estimation for the respectivepart of the FOV on which the alteration is based (e.g., steps 1705 and1709, respectively) without moving the at least one deflector to anotherinstantaneous position.

At step 1709, processor 118 estimates noise in at least some of thesignals associated with the second portion of the field of view. Asdiscussed above, processor 118 may use a variety of noise estimationtechniques, either individually or in combination, to estimate noise inat least some of the signals. Processor 118 may use the same noiseestimation technique(s) in steps 1705 and 1709 or may use differentnoise estimation technique(s) in steps 1705 and 1709. In certainaspects, processor 118 may determine that a particular noise estimationtechnique is more suitable for the first portion and that a differentnoise estimation technique is more suitable for the second portion. Forexample, processor 118 may determine that the first portion has a largernoise contribution from amplification because, for example, theamplification is higher on account of the first portion being darkerthan the second portion. In such an example, processor 118 may use adifferent technique to estimate noise in the first portion to accountfor the larger amplification noise. Examples of noise estimationtechniques are discussed below with references to FIGS. 18 and 19.Optionally, the estimation of noise in the second portion of the FOV instep 1709 may depend on the results of step 1705. Alternatively, theestimations of noises in the first portion and in the second portion ofthe FOV (steps 1705 and 1709, respectively) may be completely unrelatedand independent of each other.

In some embodiments, processor 118 may report the noise estimationsgenerated in steps 1705 and/or 1709 to another system (e.g., an externalserver). Furthermore, processor 118 may report one or more noiseindicative parameters and/or one or more noise related parameters basedon the respective noise estimation obtained by processor 118. Therespective parameter may be specific to the respective portion of theFOV, or to a larger part of the FOV that includes the respective portionof the FOV. Examples of reported parameters include, but are not limitedto, a noise estimation, one or more sensitivity settings, a detectiondistance, a detection quality indicator, and the like. In someembodiments, the report may also include one or more parametersindicative of the altered sensor sensitivity from steps 1707 and/or1711.

At step 1711, processor 118 alters a sensor sensitivity for reflectionsassociated with the second portion of the field of view based on theestimation of noise in the second portion of the field of view. Forexample, sensor sensitivity may include a signal-threshold. In someembodiments, processor 118 may increase the signal-threshold for thesecond portion relative to the signal-threshold for the first portion.Processor 118 may do so, for example, when the noise estimation in thesecond portion is higher than the noise estimation in the first portion.Accordingly, the higher signal-threshold in the first portion may filterout more of the estimated noise.

By way of example, processor 118 may estimate a level of noise onaccount of dark noise and/or amplification noise and alter a sensorsensitivity such that the sensitivity has a minimum threshold higherthan the estimated level of noise. Accordingly, the estimated noise maybe minimized, if not cancelled or eliminated, by setting the minimumthreshold. The altered sensor sensitivity for reflections associatedwith the second portion may differ from the altered sensor sensitivityfor reflections associated with the first portion.

In some embodiments, as discussed above, processor 118 may alter asensor sensitivity for reflections associated with a portion (e.g., thesecond portion) of the field of view corresponding to a singleinstantaneous position of the at least one light deflector. In otherembodiments, as discussed above, processor 118 may alter a sensorsensitivity for reflections associated with a portion (e.g., the secondportion) of the field of view corresponding to a plurality ofinstantaneous positions of the at least one light deflector.

In some embodiments, processor 118 may alter the sensor sensitivity forfirst reflections associated with the first portion received in a firstscanning cycle and alter the sensor sensitivity for the secondreflections associated with the second portion in a second scanningcycle. For example, steps 1705 and 1707 may be performed in a firstscanning cycle, and steps 1709 and 1711 may be performed in a secondscanning cycle. In certain aspects, the first scanning cycle may occurtemporally before the second scanning cycle. Alternatively, the secondscanning cycle may occur temporally before the first scanning cycle.

In other embodiments, processor 118 may alter the sensor sensitivity forfirst reflections associated with the first portion and secondreflections associated with the second portion, where the first andsecond reflections are received in a single scanning cycle. For example,steps 1705 and 1707 may be performed in the same scanning cycle as steps1709 and 1711.

Steps 1707 and/or steps 1711 may further include, after detecting anexternal light source at a first distance in the first portion, alteringthe sensor sensitivity differently for reflections associated with thefirst portion and the second portion to enable detection of an object ata second distance greater than the first distance in the second portion.Accordingly, the sensor sensitivity of the second portion may beincreased (and/or a minimum threshold decreased and/or a maximumthreshold decreased) to compensate for the external light source in thefirst portion that may result in noise in the second portion. In anotherexample, after detecting an object at a first distance in the firstportion, processor 118 may alter the sensor sensitivity to enabledetection beyond the object in the second portion. In yet anotherexample, processor 118 may alter the sensor sensitivity to enabledetection of an object in the second portion that was not visible in thefirst portion on account of the increased noise in the first portion.

By way of further example, steps 1707 and/or 1711 may further include,after detecting an external light source at a first distance in thesecond portion, altering the sensor sensitivity differently forreflections associated with the first portion and the second portion toenable detection of an object at a second distance greater than thefirst distance in the first portion. Accordingly, the sensor sensitivityof the first portion may be increased to compensate for the externallight source in the second portion that may result in noise in the firstportion.

Alternatively or concurrently, step 1711 may further includeindividually altering the sensor sensitivity for reflections associatedwith the first and second portions such that, for a same amount of lightprojected toward the first portion and the second portion, a detectiondistance associated with the second portion is higher than a detectiondistance associated with the first portion. Accordingly, the sensorsensitivity of the second portion may be increased (and/or a minimumthreshold decreased and/or a maximum threshold increased) to increasethe detection distance.

Alternatively or concurrently, steps 1707 and 1711 may further includeindividually altering the sensor sensitivity for reflections associatedwith the first and second portions such that, for a same amount of lightprojected toward the first portion and the second portion, a resolutionassociated with the second portion may be higher than a resolutionassociated with the first portion. Accordingly, the sensor sensitivitywith respect to the second portion may be increased (and/or a minimumthreshold decreased and/or a maximum threshold increased) to increasethe resolution.

For each portion of the FOV to which processor 118 altered thesensitivity setting (e.g., in steps 1707 and/or 1711), processor 118 mayalso detect an object in the respective portion of the FOV using thealtered sensitivity setting. For each portion of the FOV to whichprocessor 118 altered the sensitivity setting, processor 118 may alsogenerate a data point in a model of the scene included in the FOV (e.g.,a 2D or 3D model, such as a point-cloud model, etc.).

Method 1700 may include additional steps. For example, method 1700 mayfurther include altering the sensor sensitivity for reflectionsassociated with a third portion of the field of view differing from thefirst portion and the second portion based on the estimation of noise inthe first portion. For example, as explained above, processor 118 mayextrapolate the estimated noise from the first portion to the thirdportion. Alternatively, method 1700 may further include altering thesensor sensitivity for reflections associated with a third portion ofthe field of view differing from the first portion and the secondportion based on the estimation of noise in the first portion and thesecond portion.

In some embodiments, the extrapolation may comprise copying theestimated noise from the first portion and/or second portion to thethird portion. In other embodiments, the extrapolation may compriseapplying one or more functions to the estimated noise from the firstportion and/or second portion to generate outputs of estimated noise forthe third portion. For example, the function may depend on distancesbetween the first portion and/or the second portion and the thirdportion, a difference between an actual and/or predicted brightness ofthe first portion and/or second portion and of the third portion, adifference between a previously estimated noise in the third portion andthe currently estimated noise in the first portion and/or secondportion, or the like. The function may output estimates for the thirdportion directly, may output adjustment factors (e.g., for adding,subtracting, multiplying, or the like) for transforming the estimatednoise for the first portion and/or second portion to estimates for thethird portion, or may be convolved with or otherwise operate on theestimated noise for the first portion and/or second portion to produceestimates for the third portion or adjustment factors.

In addition to altering a sensor sensitivity, processor 118 may alsoalter one or more operational characteristic of the at least one lightsource for a portion of the FOV based on the estimation of noise in therespective portion of the FOV. For example, processor 118 may alter alight source parameter (e.g., pulse timing, pulse length, pulse size,pulse amplitude, pulse frequency, and/or the like) associated with thefirst portion such that light flux directed to the first portion isgreater than light flux directed to at least one other portion of thefield of view. Alternatively, processor 118 may alter a light sourceparameter associated with the first portion such that light fluxdirected to the first portion is lesser than light flux directed to atleast one other portion of the field of view. Processor 118 may alterthe light source parameter based on the noise estimation of step 1705and/or step 1709. For example, processor 118 may determine that lightflux directed to the first portion may be lessened because reflectionsfrom the first portion contain less noise. By way of further example,processor 118 may determine that light flux directed to the firstportion may be increased because reflections from the first portioncontain more noise. Accordingly, either individually or in combinationwith altering the sensor sensitivity, processor 118 may further accountfor noise by varying the light flux directed to a portion of the fieldof view.

By way of further example, processor 118 may increase an amount of lightprojected toward the first portion relative to an amount of lightprojected toward the second portion. Processor 118 may do so, forexample, when the noise estimation in the first portion is higher thanthe noise estimation in the second portion. As explained above,processor 118 may thus account for noise by varying the amount of lightprojected. Alternatively, processor 118 may decrease an amount of lightprojected toward the first portion relative to an amount of lightprojected toward the second portion. Processor 118 may do so, forexample, when the noise estimation in the first portion is higher thanthe noise estimation in the second portion. As explained above,processor 118 may thus account for noise by varying the amount of lightprojected.

Numerous noise estimation techniques may be used with method 1700 ofFIG. 17. FIG. 18 depicts one example of received signals with a functionfor estimating expected signals. As depicted in FIG. 18, receivedsignals 1801 represent the total signal for a portion of a field of viewthat includes noise which is received. Received signals 1801 arediscretized measurements and therefore represented as a function withdiscontinuous points of slope.

As further depicted in FIG. 18, function 1803 may represent anestimation of the expected signal without noise. For example, function1803 may be developed based on past measurements and/or on knownproperties that are being measured. For example, function 1803 may bedeveloped by processor 118 based on previously received signals in theportion of the field of view and/or based on properties of objects inthe portion of the field of view (e.g., known locations of objects,known brightness of objects, etc.). Processor 118 may derive theproperties of objects based on previously received signals.

To adjust received signals 1801 to account for noise, processor 118 mayfit received signals 1801 to function 1803. In other embodiments,function 1803 may represent a function that may be convolved with orotherwise operate on received signals 1801 to remove noise.

FIG. 19 depicts one example of received signals with a function forestimating expected signals. As depicted in FIG. 19, and similar to FIG.18, received signals 1901 represent the total signal that includes noisewhich is received. Received signals 1901 are discretized measurementsand therefore represented as a function with discontinuous points ofslope.

As further depicted in FIG. 19, function 1903 may represent anestimation of the expected noise. For example, function 1903 may bedeveloped based on past measurements and/or on known properties of theat least one sensor. For example, function 1903 may be developed byprocessor 118 based on previously received signals in the portion of thefield of view and/or based on properties of the at least one sensor(e.g., known dark noise, known amplification noise, etc.). Processor 118may derive the properties of the at least one sensor based onmanufacturing specification and/or on previous measurements.

To adjust received signals 1901 to account for noise, processor 118 maysubtract function 1903 from received signals 1901. In other embodiments,function 1903 may represent a function that may be convolved with orotherwise operate on received signals 1901 to estimate the noise fromreceived signals 1901.

Systems and methods consistent with the present disclosure may includeany appropriate noise estimation techniques and are not limited to theexamples of FIGS. 18 and 19.

Variable Flux Allocation within a Lidar FOV to Improve Detection in aRegion of Interest

By detecting laser beam reflections from real-world surroundings in itsenvironment, LIDAR system 100 can create a 3-D reconstruction of objectsin the environment within the FOV of the LIDAR system. Such LIDARsystems may have applications across a wide range of technologies. Onesuch technology, among many, is the field of autonomous andsemi-autonomous vehicles. As interest in self-driving technologycontinues to increase, LIDAR systems are increasingly being viewed asimportant components for the operation of self-driving vehicles. For aLIDAR system to be adopted by the automotive industry, the system shouldprovide reliable reconstructions of the objects in the surroundings.Thus, improvements in the operational capabilities of LIDAR systems maysolidify the LIDAR as an important contributor to realization ofautonomous navigation. Such improvements may include increases inscanning resolution, increases in detection range, and/or increases inthe sensitivity of the receiver. Such performance gains may be realizedthrough use of high energy lasers. Currently, however, use of highenergy lasers may be impractical for different reasons, such as cost,working temperature in the automotive environment, and that the maximumillumination power of LIDAR systems is limited by the need to make theLIDAR systems eye-safe (e.g., avoiding the possibility of damage to theretina and other parts of the eye that may be caused when projectedlight emissions are absorbed in the eye). Thus, there is a need for aLIDAR system that complies with eye safety regulations, but at the sametime provides performance characteristics that enhance the system'susefulness to the technological platform in which it is incorporated(e.g., self-driving vehicles, etc.).

Generally, the disclosed LIDAR systems and methods may improve systemperformance while complying with eye safety regulations. For example,through allocation of variable light power across a field of view of theLIDAR system, the disclosed systems may exhibit improvements in thequality of detections and in subsequent reconstructions in a region ofinterest (ROI). By allocating power to a field of view based on a levelof interest in a certain ROI, efficiency of the system may also beimproved even while maintaining high quality and useful data from theROI. In addition, separating FOV into different level of ROIs andallocating power to a field of view based on a level of interest in acertain ROI may bring forth many advantages. For example, it may enableLIDAR system to utilize an optical budget more efficiently by avoidingexpenditure of light projection and detection resources in areas oflower interest. It may also reduce the interferences to the surroundingenvironments (e.g. other LIDAR systems or pedestrians on the street.).Furthermore, it may simplify the computational complexity of preparingand analyzing the results and may reduce the cost associated with it. Aregion of interest may constitute any region or sub-region of a LIDARFOV. In some cases, an ROI may be determined to include a rectangularregion of a LIDAR FOV, or a region of the FOV having any other shape. Insome embodiments, an ROI may extend in an irregular pattern, which mayinclude discontiguous segments, over the LIDAR FOV. Additionally, an ROIneed not be aligned with any particular axis of the FOV, but rather maybe defined in a free-form manner relative to the FOV.

Consistent with disclosed embodiments, in FIG. 22, LIDAR system 100 mayinclude at least one processor 118, e.g., within a processing unit 108.The at least one processor 118 may control at least one light source 102in a manner enabling light intensity to vary over a scan of a field ofview 120 using light from the at least one light source. The at leastone processor 118 may also control at least one light deflector 114 todeflect light from the at least one light source in order to scan thefield of view 120. Furthermore, in some embodiments (e.g., as shown inFIG. 3), at least one light deflector 114 may include a pivotable MEMSmirror 300. The at least one processor 118 may obtain an identificationof at least one distinct region of interest in the field of view 120.Then, the at least one processor 118 may increase light allocation tothe at least one distinct region of interest relative to other regions,such that following a first scanning cycle, light intensity in at leastone subsequent second scanning cycle at locations associated with the atleast one distinct region of interest is higher than light intensity inthe first scanning cycle at the locations associated with the at leastone distinct region of interest. For example, light intensity may beincreased by increasing power per solid angle, increasing irradianceversus FOV portion, emitting additional light pulses, increasing powerper pixel, emitting additional photons per unit time, increasing theaggregated energy over a certain period of time, emitting additionalphotons per data point in a generated point cloud model, increasingaggregated energy per data point in a generated point cloud model, orany other characteristic of increasing light flux.

Disclosed system, such as LIDAR system 100, the at least one processor118 may control the at least one light source 112. For example, the atleast one processor 118 can cause the at least one light source 112 togenerate higher or lower light flux, e.g., in response to a level ofinterest associated region of interest the LIDAR FOV. Portions of fieldof view 120 that have lower interest (e.g., such as regions 30 metersaway from the road or the skyline) may be allocated with lower levels oflight flux or even no light flux at all. In other regions of higherinterest, however, (e.g., such as regions includes pedestrians or amoving car) may be allocated with higher light flux levels. Suchallocations may avoid expenditure of light projection and detectionresources in areas of lower interest, and may enhance resolution andother performance characteristics in areas of greater interest. It mayalso be possible to vary light allocation not on an object-by-objectbasis, but rather on an object-portion by object-portion basis. Forexample, in some cases, it may be more important and useful to havewell-defined information regarding the location of an edge of an object(such as the outer edge or envelope of the object, such as a vehicle).Thus, it may be desirable to allocate more light flux toward FOV regionswhere edges of the vehicle reside and less light flux toward FOV regionsthat include portions of the object residing within the externalenvelope. As just one illustrative example, as shown in FIG. 5C, the atleast one processor 118 may be configured to cause emission of two lightpulses of projected light for use in analyzing FOV regions includingedges of an object (e.g., the rounded-square object in coordinates units(B,1 ), (B,2), (C,1), (C,2) of FIG. 5C). On the other hand, for FOVregions associated with an interior of an object, or at least within anenvelope defined by detected outer edges, such as the middle region (incoordinates (C,5)) within the rounded-square object shown in FIG. 5C,less light flux may be supplied to those regions. As anotherillustrative example shown in FIG. 5C, after a first scan cycle, onlyone light pulse is supplied to the interior region of the rounded-squareshape. It should be noted that any suitable technique for increasinglight flux may be used relative to a particular region of interest. Forexample, light flux may be increased by emitting additional lightpulses, emitting light pulses or a continuous wave of a longer duration,increasing light power, etc.

The at least one processor 118 can control various aspects of the motionof at least one light deflector 114 (e.g., an angular orientation of thedeflector, an angle of rotation of the deflector along two or more axes,etc.) in order to change an angle of deflection, for example.Additionally, the at least one 118 may control a speed of movement ofthe at least one deflector 114, an amount of time the at least onedeflector dwells at a certain instantaneous position, translation of theat least one deflector, etc. By controlling the at least one lightdeflector 114, the at least one processor 118 may direct the projectedlight toward one or more regions of interest in the LIDAR FOV in aspecific way, which may enable the LIDAR system to scan the regions ofinterest in the field of view with desired levels of detectionsensitivity, signal to noise ratios, etc. As noted above, lightdeflector 114 may include a pivotable MEMS mirror 300, and the at leastone processor 118 may control an angle of deflection of the MEMS mirror,speed of deflection, dwell time, etc., any of which can affect the FOVrange and/or frame rate of the LIDAR system. It is noted that thecontrolling of the at least one light deflector 114 by the processingunit 108 may change an angle of deflection of light emitted by the LIDARsystem 100 and/or of light reflected towards the LIDAR system 100 backfrom the scene in the FOV.

During operation, the at least one processor 118 may obtain anidentification or otherwise determine or identify at least one region ofinterest in the field of view 120. The identification of the at leastone region of interest within the field of view 120 may be determinedthrough analysis of signals collected from sensing unit 106; may bedetermined through detection of one or more objects, object portions, orobject types in FOV 120; may be determined based on any of variousdetection characteristics realized during a scan of FOV 12; and/or maybe based on information received (directly or indirectly) from host 210;or based on any other suitable criteria.

As shown in FIG. 22, processing unit 108 may receive information notonly from sensing unit 106 and other components of LIDAR system 100, butmay also receive information from various other systems. In someembodiments, processing unit 108, for example, may receive input from atleast one of a GPS 2207, a vehicle navigation system 2201, a radar 2203,another LIDAR unit 2209, one or more cameras 2205, and/or any othersensor or informational system. In addition to determining one or moreparticular regions of interest within FOV 120 based on detections, etc.from LIDAR system 100, processing unit 108 may also identify one or moreregions of interest in FOV 120 based on the outputs of one or more ofGPS 2207, vehicle navigation system 2201, radar 2203, LIDAR unit 2209,cameras 2205, etc. The at least one region of interest may includeportions, areas, sections, regions, sub-regions, pixels, etc. associatedwith FOV 120.

After obtaining identification of at least one region of interest withinthe field of view 120, the at least one processor 118 may determine anew scanning scheme or may change an existing scanning scheme associatedwith light projection and subsequent detections relative to the at leastone region of interest. For example, after identification of at leastone region of interest, the at least one processor 118 may determine oralter one or more light-source parameters associated with lightprojector 112 (as described above). For example, the at least oneprocessor 118 may determine an amount of light flux to provide to aparticular region of interest, a number of light pulses to project, apower level of light projection, a time of projection for a continuouswave, or any other characteristic potentially affecting an amount oflight flux provided to a particular, identified region of interest.

The at least one processor 118 may determine particular instantaneouspositions through which deflector 114 may be moved during a scan of theat least one region of interest. Processing unit 108 may also determinedwell times associated with the determined instantaneous positionsand/or movement characteristics for moving deflector 114 between thedetermined instantaneous positions.

Prior to identifying a region of interest in the LIDAR FOV, in someembodiments, a default amount of light may be projected in each regionof the FOV during a scan of the FOV. For example, where all portions ofthe FOV have the same importance/priority, a default amount of light maybe allocated to each portion of the FOV. Delivery of a default amount oflight at each region of the FOV may involve controlling the availablelight source such that a similar number of light pulses, for example,having a similar amplitude are provided at each FOV region during a scanof the FOV. After identification of at least one region of interest,however, the at least one processor 118 may increase an amount of lightsupplied to at least one region within the region of interest relativeto one or more other regions of the FOV. In the illustrative example ofFIG. 5C, sector II may represent an identified region of interest (e.g.,because sector II is determined to have a high density of objects,objects of a particular type (pedestrians, etc.), objects at aparticular distance range relative to the LIDAR system (e.g., within 50m or within 100 m etc.), objects determined to be near to or in a pathof a host vehicle, or in view of any other characteristics suggesting aregion of higher interest than at least one other area within FOV 120).In view of sector II's status as a region of interest, more light may besupplied to the sub-regions included in sector II than the rest of theregions within the FOV. For example, as shown in FIG. 5C, sub-regionswithin sector II (other than regions determined to be occupied byobjects) may be allocated three light pulses. Other areas of lessinterest, such as sector I and sector III may receive less light, suchas one light pulse or two light pulses, respectively.

In some embodiments, a region of interest designation may depend on adistance that a target object resides relative to the LIDAR system. Thefarther away from the LIDAR system that a target object resides, thelonger the path a laser pulse has to travel, the larger the potentiallaser signal loss may be. Thus, a distant target may require higherenergy light emissions than a nearby target in order to maintain adesired signal to noise ratio. Such light energy may be achieved bymodulating the power output of source 112, the pulse width, the pulserepetition rate, or any other parameter affecting output energy of lightsource 112. Nearby objects may be readily detectable and, therefore, insome cases such nearby objects may not justify a region of interestdesignation. On the other hand, more distant objects may require morelight energy in order to achieve suitable signal to noise ratiosenabling detection of the target. Such distant objects may justify aregion of interest designation and an increase in light energy beingsupplied to respective regions of the FOV in which those objects reside.For example, in FIG. 5C, a single light pulses may be allocated todetect a first object at a first distance (e.g., either of the nearfield objects located near the bottom of FIG. 5C), two light pulses maybe allocated to detect a second object at a second distance greater thanthe first distance (e.g., the mid-field object with the rounded-squareshape), and three light pulses may be allocated to detect a third object(e.g., far field triangle object) at a third distance greater than boththe first distance and the second distance.

On the other hand, however, an available laser energy level may belimited by the eye safety regulations along with potential thermal andelectrical limitations. Thus, to ensure eye safety while using the LIDARsystem 100, the at least one processor 118 may cap accumulated light inthe at least one distinct region of interest based on eye safetythresholds. For example, the at least one processor 118 may beprogrammed to limit an amount of light projected within a distinctregion of the FOV (e.g., over a particular time duration) in order tocomply with eye safety limits. As used here, a cap may refer to athreshold light amount over a particular time duration corresponding toan upper light amount eye safety limit (or a limit set below the upperlimit to provide a margin of safety). The at least one processor 118 maycontrol the at least one light source 112 such that the cap is notexceeded during operation of LIDAR system 100. Thus, for example, aregion of lower interest may be defined in an area in which eyes arelikely to be found—e.g. in the driver area of a vehicle, in certainheights above sidewalks and bicycle lanes, etc. The lower interest inthe context of such regions does not necessarily mean that detection isless important in those regions compared to other regions, but ratherthat detection is of lower importance (or interest) than maintainingsafe operation of the system.

The at least one processor 118 may determine the identification of theat least one distinct region of interest based on information receivedfrom any suitable source. In some embodiments, the at least oneprocessor 118 may receive identification of at least one region ofinterest from at least one sensor configured to detect reflections oflight associated with the first scanning cycle. Such a sensor mayinclude, e.g., sensing unit 106, which may include one or more lightsensitive objects and one or more logic devices (e.g., processors, DSPs,gate arrays, etc.) configured to generate at least one identifier of aregion of interest or a potential region of interest. In someembodiments, the at least one processor 118 may identify a region ofinterest based on an output of sensing unit 106, for example. In otherembodiments, the at least one processor 118 may receive anidentification of a region of interest or at least one indicator of aregion of interest from one or more sources peripheral to LIDAR system100. For example, as shown in FIG. 22, such an identification orindicator may be received from vehicle navigation system 2201, radar2203, camera 2205, GPS 2207, or another LIDAR 2209. Such indicators oridentifiers may be associated with mapped objects or features,directional headings, etc. from the vehicle navigation system or one ormore objects, clusters of objects, etc. detected by radar 2203 or LIDAR2209 or camera 2205, etc. Optionally, the at least one processor 118 maydetermine the identification of the at least one distinct region ofinterest based on information received from a remote source, locatedoutside a platform on which Lidar system 100 is installed. For example,if the LIDAR system 100 is used for mapping of an environment by aplurality of vehicles, definitions on how to determine regions ofinterest may be received from a server which coordinates the operationsof the different vehicles.

In some examples, regions of interest may be determined during orsubsequent to a first scan of the FOV, and light increases to theidentified regions of interest may be accomplished in one or moresubsequent scans of the FOV. As a result, light intensity in at leastone subsequent second scanning cycle at locations associated with atleast one distinct region of interest may be higher than light intensityin the first scanning cycle at the locations associated with the atleast one distinct region of interest. In some examples, at least onesubsequent second scanning cycle of the FOV includes a plurality ofsubsequent second scanning cycles. In such cases, an aggregate lightintensity over a plurality of second scanning cycles in an area of atleast one distinct region of interest in the FOV may be greater than anaggregate light intensity in other non-regions of interest over theplurality of second scanning cycles.

By identifying regions of interest and increasing amounts of lightsupplied to those regions relative to regions of lower interest, moreobjects and/or more distant objects may be detected in the regions ofinterest as compared to regions of less interest. For example, in aregion of interest, reflections of projected light may result indetermination of an existence of a first object in the at least onedistinct region of interest at a first distance. And this first distancemay be greater than a second distance at which an object in a non-regionof interest was not detected.

The at least one processor 118 may modify illumination resolution to theat least one distinct region of interest relative to other regions. Thespatial resolution of a 3D representation of the at least one distinctregion of interest in the at least one subsequent second scanning cycleis higher than spatial resolution of a 3D representation of the at leastone distinct region of interest in the first scanning cycle. Inaddition, the at least one processor 118 may also modify illuminationtiming to the at least one distinct region of interest relative to otherregions, such that temporal resolution of a 3D representation of the atleast one distinct region of interest in the at least one subsequentsecond scanning cycle is higher than temporal resolution of a 3Drepresentation of the at least one distinct region of interest in thefirst scanning cycle. Wherein, for example, a higher temporal resolutionmay be attained by, but not limited to, increasing the frame rate; viceversa.

As aforementioned examples, when more light is allocated to the at leastone region of interest, a higher spatial and/or temporal resolution mayalso be acquired. On the other hand, for the regions of non-interest andlow interest, light allocation toward those regions may be reduced, and,in turn, a lower spatial and/or temporal resolution may be attained. Anincrease in spatial and/or temporal resolution may be achieved by, butnot limited to, using the higher light intensity (e.g. narrowing thearea of the region of interest, so that more light flux per area isallocated.) Similarly, a decrease in spatial and/or temporal resolutionmay be achieved by, but not limited to, using the lower light intensity(e.g. broadening the area of the regions of non-interest, so that lesslight flux per area is allocated.)

FIG. 20 is a flowchart of example method 2000 for detecting objects in aregion of interest using a LIDAR system. In step 2001, a processor(e.g., processor 118) controls at least one light source (e.g., lightsource 112) in a manner enabling light intensity to vary over a scan ofa field of view (e.g., field of view 120) using light from the at leastone light source. In step 2002, a processor (e.g., processor 118)controls at least one light deflector (e.g., light deflector 114) todeflect light from the at least one light source (e.g., light source112) in order to scan the field of view (e.g., field of view 120). Thedeflection of the at least one light source in step 2002 may also affectdeflection of reflected light arriving from the field of view (e.g.,field of view 120) in direction of at least one sensor (e.g., sensor116). In step 2003, a processor (e.g., processor 118) obtains anidentification of at least one distinct region of interest in the fieldof view (e.g., field of view 120). In addition, the obtainedidentification of at least one distinct region of interest in the fieldof view (e.g., field of view 120) may come from at least one sensor(e.g., sensing unit 106) configured to detect reflections of lightassociated with the first scanning cycle. Furthermore, in someembodiments, the obtained identification of at least one distinct regionof interest in the field of view (e.g., field of view 120) may be basedon a current driving mode of a vehicle in which the LIDAR system isdeployed. In some embodiments, the obtained identification of at leastone distinct region of interest in the field of view (e.g., field ofview 120) may be based on an object detected in at least one distinctregion of interest. In some embodiments, the obtained identification ofat least one distinct region of interest in the field of view (e.g.,field of view 120) may come from at least one of a GPS, a vehiclenavigation system, a radar, a LIDAR, and a camera.

In step 2004, a processor (e.g., processor 118) increases lightallocation to the at least one distinct region of interest relative toother regions, such that following a first scanning cycle, lightintensity in at least one subsequent second scanning cycle at locationsassociated with the at least one distinct region of interest is higherthan light intensity in the first scanning cycle at the locationsassociated with the at least one distinct region of interest. Inaddition, the at least one subsequent second scanning cycle includes aplurality of subsequent second scanning cycles, and an aggregate lightintensity in an area of the at least one distinct region of interestover a plurality of second scanning cycles is greater than an aggregatelight intensity in other non-regions of interest over the plurality ofsecond scanning cycles.

In step 2005, a processor (e.g., processor 118) adjusts light allocationsuch that in a single scanning cycle more light is projected towards theat least one distinct region of interest relative to the other regions.In some circumstances, a processor (e.g., at least one processor 118)may allocate less light in the at least one subsequent second scanningcycle to a plurality of regions identified as non-regions of interestrelative to an amount of light projected towards the plurality ofregions in the first scanning cycle.

FIG. 21 is a flowchart of example method 2100 for detecting objects in aplurality of regions of interest using a LIDAR system. In step 2001, aprocessor (e.g., processor 118) controls at least one light source(e.g., light source 112) in a manner enabling light intensity to varyover a scan of a field of view (e.g., field of view 120) using lightfrom the at least one light source. In step 2002, a processor (e.g.,processor 118) controls at least one light deflector (e.g., lightdeflector 114) to deflect light from the at least one light source(e.g., light source 112) in order to scan the field of view (e.g., fieldof view 120). In step 2003, a processor (e.g., at least one processor118) obtains an identification of at least one distinct region ofinterest in the field of view (e.g., field of view 120). In addition,the obtained identification of at least one distinct region of interestin the field of view (e.g., field of view 120) may come from at leastone sensor (e.g., sensing unit 106) configured to detect reflections oflight associated with the first scanning cycle. Furthermore, in someembodiments, the obtained identification of at least one distinct regionof interest in the field of view (e.g., field of view 120) may be basedon a current driving mode of a vehicle in which the LIDAR system isdeployed. In some embodiments, the obtained identification of at leastone distinct region of interest in the field of view (e.g., field ofview 120) may be based on an object detected in at least one distinctregion of interest. In some embodiments, the obtained identification ofat least one distinct region of interest in the field of view (e.g.,field of view 120) may come from at least one of a GPS, a vehiclenavigation system, a radar, a LIDAR, and a camera.

In step 2101, a processor (e.g., processor 118) may rank the pluralityof regions of interest. For example, a scene may be scanned by a LIDARsystem. The regions of interest of the scene may be designated as eitherbeing a region of non-interest (RONI) or a region of interest (ROI) thathas a level of interest between low and high. For example, roaddelimiters and vertical planes of buildings may be designated as beingregions of high interest (R2), pedestrians and moving cars may bedesignated within regions of medium interest (R1), and the rest of thescene may be generally considered a region of low interest (R0). Theskyline may be designated as a RONI (R3).

In step 2103, a processor (e.g., processor 118) allocates light based onthe ranking, wherein an amount of light allocated to a highest rankingregion of interest may be greater than an amount of light allocated tolower ranking regions of interest. For example, the power or resourceallocation for the illustrative scene described above may be determinedby a processor. Based on the rank, the processor may allocate most powerto the region of highest interest R2, then to the region of mediuminterest R1 and may provide the lowest allocation to the low interestregion R0. Some power may also be allocated to RONI R3 in order toperiodically confirm that it is still a RONI. In this example, region 2(R2) may be defined as the most interesting region. It may be attributedwith the highest quality of service, largest laser power, highestreceiver sensitivity, highest angular scan resolution, highest rangeresolution, highest frame rate, etc. implying the longest rangedetection capability.

In step 2004, a processor (e.g., processor 118) may increase lightallocation to the at least one distinct region of interest relative toother regions, such that following a first scanning cycle, lightintensity in at least one subsequent second scanning cycle at locationsassociated with the at least one distinct region of interest may behigher than light intensity in the first scanning cycle at the locationsassociated with the at least one distinct region of interest. Inaddition, the at least one subsequent second scanning cycle may includea plurality of subsequent second scanning cycles, and an aggregate lightintensity in an area of the at least one distinct region of interestover a plurality of second scanning cycles may be greater than anaggregate light intensity in other non-regions of interest over theplurality of second scanning cycles.

In step 2005, a processor (e.g., processor 118) adjusts light allocationsuch that in a single scanning cycle more light is projected towards theat least one distinct region of interest relative to the other regions.In some circumstances, a processor (e.g., processor 118) may allocateless light in the at least one subsequent second scanning cycle to aplurality of regions identified as non-regions of interest relative toan amount of light projected towards the plurality of regions in thefirst scanning cycle.

Adaptive Lidar Illumination Techniques Based on Intermediate DetectionResults

FIG. 23 illustrates an exemplary embodiment of a LIDAR system 2300 thatemits light and detects photons reflected from a field-of-view of theLIDAR. In some embodiments, LIDAR system 2300 may operate as describedabove with reference to LIDAR system 100. Based on the detectionresults, the LIDAR may generate a sequence of depth maps. As previouslydescribed, the LIDAR may be operable to generate depth maps of one ormore different types, such as any one or more of the following types:point cloud model (PC), polygon mesh, depth image (holding depthinformation for each pixel of an image or of a 2D array), or any othertype of 3D model of a scene.

The generated depth maps may include a temporal characteristic. Forexample, the depth maps may be generated in a temporal sequence, inwhich different depth maps are generated at different times. Each depthmap (interchangeably “frame”) of the sequence may be generated withinthe duration of a scan of the LIDAR FOV. In some embodiments, such scansmay occur within a period of several seconds, within about 1 second, orless than a second.

In some embodiments, LIDAR system 2300 (interchangeably “the LIDAR”) mayhave a fixed frame rate over the sequence (e.g. 10 frames persecond—FPS—25 FPS, etc.) or a dynamic frame rate. The frame-times ofdifferent frames are not necessarily identical across the sequence. Forexample, a 10 FPS LIDAR may generate one depth map in 100 milliseconds(the average), the next frame in 92 milliseconds, a third frame at 142milliseconds, and additional frames at a wide variety of rates averagingto the 10 FPS specification.

The frame time may refer to the span of time starting with the firstprojection of light whose detection gives rise to the detectioninformation of the frame and ending with the finalization of therespective depth map (“frame”). A “frame-illumination-duration” is thespan of time starting with the first projection of light whose detectiongives rise to the detection information of the frame, and ending whenthe last photon whose detection impacts the detection information of theframe is emitted (i.e. the “frame-illumination-duration” is the firstpart of the respective frame-time, followed by a duration of at leastsome processing of detection information of the frame to yield therespective depth-map). In some embodiments, all actions, processes orevents which are described in the present disclosure as happening in thesame frame-time, may be required to happen in the sameframe-illumination-duration (i.e. stricter time-constrains may beimplemented).

In some embodiments, the frame-times may partly overlap (e.g. theprocessing of an N^(th) depth-map may extend into the lighting of an(N+1)^(th) frame), but optionally may be completely nonoverlapping. Insome embodiments, there may be time gaps between the frame-times ofdifferent frames.

The number of depth maps in the sequence may be equal or greater than 3,even though significantly longer sequences of frames may be generated bythe LIDAR. For example, the sequence may include more than 10 depthmaps. For example, the sequence may include more than 100 depth maps.For example, the sequence may include more than 1,000 depth maps. It isnoted that the sequence does not necessarily include all of the frameswhich are generated by the LIDAR. Optionally, the sequence of depth mapsmay include all of the depth maps generated by the LIDAR between thefirst and the last depth maps of the sequence.

System 2300 may include at least sensor-interface 2350 and light sourcecontroller 2360, but may also include additional components, such as(but not limited to) the ones discussed below. Sensor-interface 2350 maybe configured and be operable to receive from one or more sensors of theLIDAR (e.g. sensors 2344(1), 2344(2) and 2344(3)) detection-informationwhich is indicative of amount (or amounts) of light detected by therespective sensor(s) (e.g. number of detected photons, accumulatedenergy of detected light, etc.). The light detected by the sensors mayinclude—for at least some of the segments of the field-of-view (FOV) ofthe LIDAR—photons emitted by the LIDAR and reflected back from a scenetoward one or more detectors of the LIDAR.

The FOV of the LIDAR may include several segments (two or more, up tothe hundreds or thousands, and possibly more) that are illuminated indifferent timings. Each segment may include one or more items of thedepth map (e.g. one or more polygons, one or more point-cloud points,one or more depth image pixels), and may be covered by one or moresensors (generating one or more detection signals). In some embodiments,the segments of the FOV may include non-overlapping segments. In otherembodiments, some of the segments of the FOV may partly overlap eachother. Optionally, the depth map may not include an item for one or moresegments (e.g. because no photons reflected within the allowed timeframe, or the SNR was too low for detection). In such cases, the depthmap may include a corresponding indication of lack of data, but notnecessarily so.

In some embodiments, the depth map generated by the LIDAR may includedepth information based on detection of light from segments which areilluminated without processing of preliminary illumination (e.g. as maybe implemented with regard to the optional distinction between centralsegments and circumference segments). The depth map generated by theLIDAR may include depth information also for parts (or segments) of theFOV which are not illuminated and/or which is not based on detection oflight. For example, some items of the depth map (pixel, PC point,polygon or part thereof) may be based on interpolation or averaging ofdetection-based values determined for illuminated parts of the FOV.

In an exemplary embodiment, sensor-interface 2350 is operable to receive(from one or more sensors of the LIDAR), in each of the frame-times ofthe sequence and for each segment out of a plurality of segments of afield-of-view of the LIDAR, preliminary detection-information of lightemitted by the LIDAR during the respective frame-time and reflected (orotherwise scattered) from the respective segment. For some of thesegments, no light projected by the LIDAR may be reflected (e.g. if notarget is within a detection range of the LIDAR), but for at least someof the segments the preliminary detection-information may be indicativeof amount of projected light that is reflected from the scene anddetected by one or more sensors of the LIDAR. Along with thedetection-information provided by the one or more sensors (including thepreliminary detection-information), the signals generated by the one ormore sensors may include contributions from, for example, externalradiation (e.g. sunlight, flashlights, and other sources oflight/radiation other than the LIDAR system 100) and sensor noise (e.g.dark current).

The preliminary detection-information may be obtained as a single signal(based on the outputs of one or more sensors—e.g. one or more SPADs, oneor more APDs, one or more SiPMs, etc.) or as a plurality of signals(e.g., the outputs of multiple sensors). The preliminarydetection-information may include analog and/or digital information. Thepreliminary detection-information may include a single value and/or aplurality of values (e.g. for different times and/or parts of thesegment). The preliminary detection-information may pertain to one ormore items of the depth map (e.g. to one or more polygons, to one ormore point-cloud points, to one or more depth image pixels, etc.). It isnoted that the preliminary information may be later used for thedetermining of the distance to at least one object in the FOV.

Light-source controller 2360 may be configured and operable to control alight source 2310 of the LIDAR, and especially to control emission oflight by the light source 2310. Light-source controller 2360 may be theonly entity which controls emission of light by the light source 2310 ofthe LIDAR, but this is not necessarily so. If the LIDAR includes morethan one light sources, light-source controller 2360 may be configuredand operable to control one or more of these light sources, possibly allof them. Additionally, various controllers other than controller 2360may control or influence at least one operational aspect of a lightsource associated with LIDAR system 100.

In some embodiments, light-source controller 2360 is configured tocontrol, in each of the frame-times of the sequence, subsequent emissionof light by the LIDAR. The subsequent emission is emitted (if itsemission is permitted by light-source controller 2360) after theemission of the preliminary light emission (the emission which is usedfor the preliminary detection-information). If the LIDAR emits pulsedlight, than the subsequent emission of light may include one or morepulses of light.

Light-source controller 2360 may be configured to control in each of theframe-times of the sequence, based on the preliminarydetection-information of each segment out of the plurality of segments,subsequent emission of light by the LIDAR to the respective segmentduring the respective frame-time. That is—in each frame time,light-source controller 2360 may control subsequent emission of light ineach segment out of a plurality of segments—based on detection andprocessing of light which was emitted by the LIDAR in the sameframe-time, and which was detected in the same segment.

The controlling of the emission of subsequent light per segment of theFOV allows differentiation in the projecting of light to differentsegments of the LIDAR's FOV, based on detection of reflected light fromthe same frame—indicative of detection results (e.g. of targets indifferent parts of the FOV) with almost instantaneous inputs. Thisdifferentiation may be used to accomplish various goals, such as—

-   -   a. Eye safety (and other safety consideration such as skin        safety, safety of optical systems, safety of sensitive materials        and objects on so on): it is possible to limit emitted power        levels in one or more portions of the LIDAR FOV where safety is        a consideration, while emitting higher power levels (thus        potentially improving signal-to-noise ratio and detection range)        to other parts of the FOV.    -   b. Power Management: It may be possible to direct more energy        towards parts of the LIDAR FOV were it will be of greater use        (e.g. regions of interest, further distanced targets, low        reflection targets, etc.) while limiting lighting energy        delivered to other parts of the FOV. Such light allocation for        either eye safety or power management (or any other purpose) may        be based on detection results from a current frame or any        preceding frame.

In some embodiments, controlling of the emission of subsequentprojections of light to a particular segment or region of the FOV mayinclude controlling (e.g., altering) one or more parameters of the lightsource to impact subsequent light emissions. Such alterations may impactvarious characteristics of the projected light, such as (though notlimited to) any one of the following:

-   -   a. increasing, reducing, limiting, or precluding light        projection to any one or more LIDAR FOV segments during a        current scan of the FOV or during subsequent scans of the FOV;    -   b. overall light energy supplied to across the FOV or to any        portion of the FOV;    -   c. an energy profile of light supplied to any portion of the        FOV;    -   d. a duration of light emissions;    -   e. wave properties of the light projected to any portion of the        FOV, such as polarization, wavelength, etc.

In addition, FIG. 23 illustrates a plurality of segments of the FOV. Itwill be clear to a person who is skilled in the art that each segmentmay represent a three-dimensional conic section (in essence a cone or atruncated cone). For simplicity of illustration, only a cross section ofeach segment is illustrated. Additionally, the number of segments andtheir spatial configuration may be significantly different. For example,the segments in the illustration are arranged in a 3 by 6 2D rectangulararray, but other non-rectangular arrangements may be used instead, aswell as 1D arrangements.

System 2300 may be adapted to control inspection of (and possibly alsoto inspect) regions or segments of a scene (shown here is a specificfield of view (FOV) being scanned) using light pulses (or other forms oftransmitted light such as CW laser illumination). The characteristics ofthe illumination (initial illumination, subsequent illumination, or anyother illumination by the LIDAR) may be selected (possibly also duringoperation of the LIDAR) as a function of any one or more of thefollowing parameters (among others):

-   -   a. Optical characteristics of the scene segment being inspected.    -   b. Optical characteristics of scene segments other than the one        being inspected.    -   c. Scene elements present or within proximity of the scene        segment being inspected.    -   d. Scene elements present or within proximity of scene segments        other than the one being inspected.    -   e. An operational mode of the scanning or the steering device.    -   f. A situational feature/characteristic of a host platform with        which the scanning or the steering device is operating.

The light source 2310 of the LIDAR (interchangeably “emitter” and“emitter assembly”) may include one or more individual emitters (e.g.one or more lasers, one or more LEDs), which may operate using similaror different operational parameters (e.g. wavelength, power, focus,divergence, etc.). Light-source controller 2360 may control one, some orall of the individual emitters of light-source 2310. In someembodiments, the light source 2310 may be operable to emit photonicinspection pulses toward the FOV. In some embodiments, the light sourceand deflector may be combined. For example, the LIDAR system may includea vertical-cavity surface-emitting laser or an optical phased array.

The sensor assembly 2340 of the LIDAR (interchangeably “sensor array”,“sensor”, “detector array” and “detector assembly”) may include one ormore light sensitive detectors 2344, each of which may includeindividual sensing units. For example, each detector 2344 may be aSilicon photomultiplier (SiPM) which includes a plurality ofSingle-photon avalanche diodes (SPADs). The sensor assembly detectsphotons emitted by the LIDAR which are reflected back from objects of ascanned scene.

In some embodiments, the LIDAR may further include a steering assembly2330 for directing the emitted light in a direction of a scanned scenesegment, and/or for steering the reflected photons towards the sensorarray 2340. The steering assembly 2330 may include controllablysteerable optics (e.g. a rotating/movable mirror, rotating/movablelenses, etc.), and may also include fixed optical components such asbeam splitters, mirrors and lenses. Some optical components (e.g. usedfor collimation of the laser pulse) may be part of the emitter, whileother optical components may be part of the detector assembly. In someembodiments the steering assembly 2330 may contain an array of mirrors.

In some embodiments, light-source controller 2360 may be connected tothe light-source 2310 in different ways, such as by electrical circuitryor other wired connection, by wireless connection, etc. Light-sourcecontroller 2360 may also be connected to steering assembly 2330, forcontrolling a steering direction of emitted and/or reflected light,based on analysis of the preliminary detection information. For example,if no subsequent illumination is needed for a given segment, thesteering assembly may be instructed to immediately change to anothersteering state, in order to illuminate another segment of the scene.

A controller 2320 of the LIDAR may be implemented for controlling thesensing array 2340, the steering assembly 2330 and/or other componentsof the LIDAR. Controller 2320 may include light-source controller 2360,but light-source controller 2360 may also be external and/or independentof controller 2320 (e.g. host 230). In the latter case, it is possiblethat the light-source may be controlled by both controller 2320 andlight-source controller 2360. Controller 2320 may optionally be used inorder to regulate operation of the emitter 2310, the steering assembly2330 and the sensor assembly 2340 in a coordinated manner and optionallyin accordance with scene segment inspection characteristics (e.g. basedon internal feedback, host information, or other sources).

According to some embodiments, inspection of a scene segment by theLIDAR may include illumination of a scene segment (interchangeably“segment”, “region” and “scene region”) with transmitted light (e.g. apulse of photons). The emitted light may have known parameters such as:duration, angular dispersion, wavelength, instantaneous power, photondensity at different distances from the emitter, average power, powerintensity, pulse width, pulse repetition rate, pulse sequence, dutycycle, wavelength, phase, polarization and more.

Inspection of the region may also include detecting reflected photons,and characterizing various aspects of these reflected inspectionphotons. The reflected inspection photons may include photons of theemitted light reflected back towards the LIDAR from an illuminatedelement present within the scanned scene segment.

The reflected photons may result from inspection photons and the sceneelements they are reflected from, and so the received reflected signalmay be analyzed accordingly. By comparing characteristics of emittedlight with characteristics of a corresponding reflected and detectedsignal, a distance and possibly other physical characteristics (such asreflected intensity) of one or more scene elements present in thescanned scene segment may be estimated. By repeating this process acrossmultiple parts of the FOV (e.g. in a raster pattern, Lissajous patternor other patterns), an entire scene may be scanned in order to produce adepth map of the scene.

A “scene segment” or “scene region” may be defined, for example, usingangles in a spherical coordinate system, for example, corresponding to abeam of light in a given direction. The light beam having a centerradial vector in the given direction may also be characterized byangular divergence values, spherical coordinate ranges of the light beamand more.

In some embodiments, the different segments as defined in the context ofillumination are not necessarily identical to the size of FOV portionsor parts which are differentiated in the context of detection (e.g.“pixels” or the depth map). For example, the LIDAR may generate an N byM depth map (e.g. a 100 by 100 depth image), but partition the same FOVinto less segments (e.g. 10 by 10 or 20 by 1) for the illumination. Inanother example, an illumination segment may be narrower in at least onedimension than the angular resolution of detection.

In some embodiments, range estimator 2390 obtains detection informationacquired by the sensor array 2340, and processes the information inorder to generate the depth map. The processing may be based ontime-of-flight analysis, or in any other way known in the art.

The preliminary detection-information may be based on detection by aplurality of detectors (e.g. pixels. SiPMs) of a concurrent emission(e.g. one or more pulses, or a spatially continuous illumination).Light-source controller 2360 may determine, based on the preliminarydetection-information generated by the plurality of detectors (e.g.2340), how to collectively control subsequent emission which isdetectable by all of the respective detectors. In some embodiments, thelight-source controller 2360 may block any subsequent emission to anentire segment—even if only one or some of the detectors (but not all)indicate that projecting to the respective segment is not safe.

FIG. 24 is a flow chart illustrating an example of method 2400, inaccordance with presently disclosed embodiments. Method 2400 is a methodfor controlling operation of a Light Detection and Ranging device(LIDAR) which generates a sequence of depth maps. Each depth map of thesequence may be generated in a corresponding subsecond frame-time. Insome embodiments, method 2400 may be executed on a pixel-by-pixel orbeam-spot by beam-spot basis.

Referring to the examples set forth with respect to the previousdrawings, method 2400 may be executed by system 2300. Method 2400 mayinclude executing any functionality, process, capability, etc. discussedwith respect to system 2300, even if not explicitly stated. Likewise,system 2300 may be configured, adapted and/or operable to incorporateany step or variation of method 2400, even if not explicitly stated.

Method 2400 may include executing in each of the frame times of thesequence, for each segment out of a plurality of segments of afield-of-view of the LIDAR, at least stages 2440 and 2450. In someembodiments, method 2400 may or may not include executing stages 2440and 2450 for all of the segments in the FOV. In other embodiments,method 2400 may or may not include executing stages 2440 and 2450 forall of the illuminated segments of the FOV.

Stage 2440 may include: obtaining preliminary detection-information(e.g. in one or more signals) based on light emitted by the LIDAR duringthe respective frame-time and reflected from the respective segment.Obtaining preliminary detection-information may include obtainingdetection information for a single pixel of the depth image (or an itemof another type of depth map, such as a PC point or a polygon, surface,face, edge or vertex of a polygon mesh), or for more than one pixel (oritem). Referring to the examples set forth with respect to the previousdrawings, stage 2440 may be executed by sensor interface 2350 and/or bysensor assembly 2340.

Stage 2450 may include: selectively controlling, based on thepreliminary detection-information (of stage 2440, for the same segmentin the same frame-time), subsequent emission of light by the LIDAR to arespective segment during the same respective frame time. Referring toexamples set forth with respect to the previous drawings, stage 2450 maybe executed, e.g., by light source controller 2360. The controlling ofstage 2450 may include, for example, any form of controlling discussedwith respect to light source controller 2360. In some embodiments, stage2450 may include controlling a steering assembly of the LIDAR (e.g.steering assembly 2330) to direct the subsequent emission to therespective segment.

In some embodiments, in each frame-time the obtaining of the preliminarydetection-information and the selective controlling (for all of thesegments) are executed within the same frame-illumination-duration(which is the time between the emissions of the first photon in theframe-time to the emission of the last photon whose detection affectsthe depth map of the frame). Optionally, the selective controlling andthe subsequent emission are finished before a processing of detectioninformation for the generation of the depth map of the frame-timebegins.

In some embodiments, different orders in which different segments areilluminated and analyzed may be implemented. For example, preliminarilyilluminating each segment, obtaining the respective preliminarydetection information (stage 2440) and selectively controlling thesubsequent illumination to the same segment (stage 2450) may proceedbefore proceeding to execute the same steps for another segment.

In another embodiment, between a preliminary illumination of a firstsegment to its subsequent illumination (with the respective subsequentemission), another segment may be illuminated. In some embodiments, thesubsequent emission for a single segment is preceded by a segmentdark-time of the single segment (i.e. during which the LIDAR does notproject any light to that segment), during which another segment of theplurality of segments is illuminated by the LIDAR.

Method 2400 may be used for ensuring that LIDAR system 100 is eye-safe(e.g. operates according to the requirements of any relevant eye safetyregulations). In some embodiments, the selective controllingillumination is preceded by a stage (not illustrated) ofdetermining-based on the preliminary detection-information—that aprojection field (e.g. spherical sector, a cone or a truncated cone) isclear of people at least within an eye-safety range for at least apredetermined number of frames. This way, LIDAR system 100 may preventsubsequent emission whose power exceeds a safety threshold for portionsof the FOV that were not clear of people. The eye-safety range (e.g.“range threshold” of FIG. 23) may be a predetermined range, but notnecessarily so. In some cases, processor 118 may be configured to adjustthe threshold associated with the safety distance based on reflectionssignals received based on one or more light projections to a particularregion of the LIDAR FOV (either based on an initial light projection ora subsequent light projection having at least one characteristic alteredwith respect to the initial light projection).

Depending on the detected conditions or scenario, the selectivecontrolling of stage 2450 may include controlling projection ofsubsequent light emissions to the projection field that do or do notfall below an eye safety illumination limit, but in all casescontrolling of the illumination may be performed in a manner whichcomplies with eye safety regulations. For example, where LIDAR detectionindicate a lack of eye bearing individuals (human or otherwise) in aparticular region or regions of the LIDAR FOV, subsequent lightprojections within that region or regions may proceed at levels thatwould not ordinarily be eye-safe. Should an eye bearing individual besubsequently detected, e.g., entering the region or regions not previousoccupied by such individuals, then one or more parameters of the lightprojector may be altered such that subsequent light emissions to theoccupied region may be performed in a manner safe for the individual'seyes. In other cases, one or more eye bearing individuals may bedetected within a particular region of the LIDAR FOV, but at a distancebeyond an eye safety threshold (e.g., an ocular hazard distance). Insuch cases, light may be projected to that region in a manner that maynot be eye-safe within the eye safety threshold, but that is eye-safebeyond the eye-safety threshold where the individuals are detected. Instill other cases, humans and/or animals may be detected at a rangewithin an immediate area of the LIDAR system (e.g., within apredetermined eye safety threshold distance). In such cases, lightprojections may be altered to maintain eye safety in those regions inthe immediate area of the LIDAR where one or more eye bearingindividuals are detected. Eye-safety protocols may define a maximumpower level or a threshold of accumulated energy over time. If asubsequent light emission includes a group of pulses, for example, eyesafety compliance may require that the aggregate energy of those pulsesnot exceed a predetermined threshold level. In some cases, when anobject (e.g., a person) is detected in an immediate area of the LIDARsystem, processor 118 may be configured to prevent any further lightemission toward a portion of the immediate area associated with thedetected object. In other cases, when an object is detected in theimmediate area, the at least one processor may be further configured toregulate at least one of the at least one light source and the at leastone light deflector to emit visible light toward the immediate area. Itis noted that the visible light may be emitted by a separate lightsource that the light source whose light is used in the determination ofdistances.

The term “immediate area” is widely used in the art, and should bebroadly construed to include an area in proximity to the LIDAR system.The size of the immediate area may depend on the power settings of theLIDAR system (which effect the potential hazard distance of the LIDARsystem). The immediate area may be of substantially the same diameter inall directions of the FOV (to which light may be emitted by the LIDARsystem)—for example having differences of up to 50%—but this is notnecessarily so. Optionally, the immediate area of the LIDAR system isdefined in all directions of the FOV to which light may be emitted bythe LIDAR system.

In some embodiments, based on light projected to selected regions of theLIDAR FOV, a processor, such as processor 118, may receive from at leastone sensor reflections signals indicative of light reflected fromobjects in the LIDAR FOV. Processor 118 may determine, based on thereflections signals resulting from an initial light emission, whether anobject is located in an immediate area of the LIDAR system (e.g., in aregion associated with a particular segment of the LIDAR FOV or group ofsegments of the FOV and within a threshold distance from the at leastone light deflector). The threshold distance may be associated with asafety distance, such as an eye safety distance. When no object isdetected in the immediate area of the FOV, processor 118 may control theat least one light source such that an additional light emission may beprojected toward the immediate area, thereby enabling detection ofobjects beyond the immediate area. In such cases, for example, the atleast one processor may be configured to use an initial light emissionand an additional light emission to determine a distance of an objectlocated beyond the immediate area. It is noted that the term“reflections signals” should be broadly interpreted to include any formof reflection and of scattering of light, including specularreflections, diffuse reflections, and any other form of lightscattering.

When an object is detected in the immediate area, processor 118 mayregulate at least one of the at least one light source and the at leastone light deflector to prevent an accumulated energy density of thelight projected in the immediate area to exceed a maximum permissibleexposure. For example, various parameters of the light projecting unitand/or the light deflecting unit may be altered to provide an additionallight emission to a particular LIDAR FOV segment that is different froman initial light emission in at least one aspect (e.g., differing in atleast one aspect relating to an eye safety parameter). The additionallight emission may be made to the particular LIDAR FOV segment eitherduring the same FOV scan as when the initial light emission is made orduring any subsequent FOV scan.

As LIDAR systems may be capable of determining distance values todetected objects, this information may be leveraged by the LIDAR systemfor compliance with eye safety regulations. For example, once an objectis detected, processor 118 may determine a distance to the object (e.g.,based on time of flight analysis, etc.). Processor 118 may calculate anintensity of projected light at the detected object (e.g., based on thedetected distance and known characteristics of the light projected fromsource 112/deflector 114). Based on this calculation, processor 118 maydetermine a light exposure time that is eye-safe at the distance to theobject. Processor 118 may then control at least one of light source 112and deflector 114, to ensure that the light exposure time is notexceeded. Similarly, processor 118 may be configured to determine avalue associated with the maximum permissible exposure, and thisdetermination may be based on a determined distance between the at leastone light deflector and the object detected in the immediate area of theLIDAR system.

In addition or instead to determination of exposure time, processor 118may determine a permissible light energy that is eye-safe at thedistance to the object based on the aforementioned calculation of theintensity. For both exposure time and permissible light energy, it isnoted that in some examples, processor 118 may determine the respectiveparameter indirectly, by determining a value which is indicative of therespective parameter. It is noted that the determination of permissiblelight energy (if implemented) may be used in the same way the determinedexposure time is used, mutatis mutandis, even if not explicitlyelaborated.

It is also noted that the distance between the at least one lightdeflector and the object may be determined directly or indirectly.Indirect determination of that distance may be achieved, for example, bydetermining another distance, such as the distance between at least onelight source to the object.

In embodiments where the LIDAR FOV is divided into segments or sectorsfor performing scans of the FOV, for example, each segment or sector maybe associated with a different immediate area relative to the LIDARsystem. That is, each segment or sector, along with an eye safetythreshold distance, may define a separate immediate area in the vicinityof the LIDAR system. In some embodiments, processor 118 may beconfigured to determine, based on reflections signals resulting frominitial light emissions to each sector, whether an object is located ineach of the immediate areas associated with the plurality of sectors. Insome cases and based on reflections signals received from a particularsector via the sensor unit, processor 118 may be configured to detect anobject in a first immediate area associated with a first sector.Similarly, processor 118 may be configured to determine an absence ofobjects in a second immediate area associated with a second sector. Insuch as case, the at least one processor 118 may be configured tocontrol (e.g., in a single scanning cycle) the at least one light sourcesuch that an additional light emission is projected toward the secondimmediate area. Further, processor 118 may regulate at least one of thelight source and/or the light deflector to prevent an accumulated energydensity of the light in the first immediate area to exceed a maximumpermissible exposure.

In some embodiments where the LIDAR FOV is divided into sectors,processor 118 may be configured to determine, based on reflectionssignals associated with an initial light emission from each sector,whether an object is located in each of the immediate areas associatedwith the plurality of sectors. Upon detecting an object in a firstimmediate area associated with a first sector and determining an absenceof objects in a second immediate area associated with a second sector,processor 118 may control the at least one light source such that in asingle scanning cycle, an additional light emission may be projectedtoward the second immediate area. Processor 118 may also regulate atleast one of the at least one light source and the at least one lightdeflector to prevent an accumulated energy density of the light in thefirst immediate area to exceed the maximum permissible exposure.

It should be noted that any of the LIDAR system embodiments describedabove may be used in conjunction with the eye safety light projectionprotocols described here. For example, in some embodiments an eye safeLIDAR may include a monostatic deflector configuration such that adeflector steers projected light toward a particular segment of thefield of view while light reflected from objects in the particularsegment of the field of view is directed toward one or more sensors bythe same deflector. Additionally, the light deflector may include aplurality of light deflectors, and processor 118 may be configured tocause the plurality of light deflectors to cooperate to scan the LIDARFOV. In some embodiments, the at least one light deflector may include asingle light deflector, and the at least one light source may include aplurality of light sources aimed at the single light deflector.

Various different light sources may be employed in the LIDAR system 100.For example, in some cases, the light source may be configured toproject light at a wavelength less than 1000 nm, between 800 nm and 1000nm, etc.

In some embodiments, LIDAR system 100 may include more than one lightsource. In such cases, each light source may be associated with adiffering area of the LIDAR FOV. Processor 118 may be configured tocoordinate operation of the at least one light deflector and theplurality of light sources such that when one object is detected in afirst area of the field of view at a distance greater than the safetydistance, energy density of light projected by a different light sourceto a second area of the field of view does not surpass a maximumpermissible exposure associated with the second area of the field ofview.

Additionally, processor 118 may be configured to coordinate the at leastone light deflector and the at least one light source such that whenanother object is detected in another area at a distance greater thanthe safety distance, energy density of light projected by the at leastone light source to the another portion of the field of view does notsurpass a maximum permissible exposure associated with the anotherportion of the field of view. In some embodiments, the safety distanceis a Nominal Ocular Hazard Distance (NOHD).

In some embodiments, the selective controlling of stage 2450 may includepreventing—in at least one segment during at least oneframe-time-subsequent emission whose power exceeds a safety threshold,for projection fields which were not clear of people for at least apredetermined number of frame-times. In some embodiments, the selectivecontrolling for at least one FOV segment in at least one frame-time mayinclude maintaining or even increasing a light projection power level,while at the same time decreasing an accumulated energy amount providedto the at least one FOV segment. For example, in a pulsed laser example,the pulse (or pulses) of a preceding illumination may have the same peakpower (or even a lower power level) as the pulse (or pulses) of one ormore subsequent emissions. Still, however, an accumulated energy of thesubsequent illumination may nevertheless be lower than the accumulatedenergy of the preceding emission or emissions. In such a manner, it maybe possible to increase a signal to noise ratio and/or a detection rangewhile still operating in compliance with eye safety regulations. Ofcourse, in other instances, it may be possible to vary the power level,accumulated energy characteristics, or any other light emissionparameter in any combination in order to accomplish LIDAR detectiongoals while complying with eye safety regulations.

In some embodiments, the selective controlling of stage 2450 may includestopping (or preventing) a subsequent light emission to a particular FOVsegment or group of segments within any given frame-time to comply witheye safety regulations. Such control may also be implemented to reduceor eliminate a risk of saturation of the detector, or any othercomponent of the detection and/or processing chain. Such control canalso support power conservation considerations (e.g. not spending energywhere it is not required, e.g. if an object can be detected and/or arange can be determined based on previous emissions and withoutcontinued emissions).

In some embodiments, the selective controlling for at least one segmentof the LIDAR FOV in at least one frame-time may include preventingemission of any subsequent emission if the preliminarydetection-information fulfills a predetermined detection criterion. Insome embodiments, the selective controlling may be followed by furtherprocessing of the preliminary detection information (without any furthersubsequent detection information for the respective segment), to yielddepth information for the segment.

Regarding eye safety (for example), method 2400 may be used to preventillumination of potentially harmful emissions to FOV regions where oneor more objects are detected based on a determined likelihood that theone or more objects includes a human and/or animal. Potentially harmfulemissions to the particular FOV region may be suspended even if there isonly a low likelihood that the one or more objects includes an eyebearing individual. Potentially harmful emissions to a particular FOVmay also be suspended (or otherwise altered) even in situations where noindividuals (or even objects) are detected if the FOV region isdetermined (e.g., based on detected context, such as near a stopped bus,near a cross walk, near a sidewalk, near a building entrance, etc.) tobe a region where eye bearing individuals are commonly found. In otherregions of the FOV not determined to include eye bearing individuals orexpected/predicted to include such individuals, higher power emissionsmay be provided to those regions. As a result, a generated depth map maybenefit from detections in those areas not subject to eye safetylimitations (e.g., because of higher power emissions, etc.), such thatthe overall quality of the depth map may be higher than if every lightemission across the entire FOV was made at power levels etc. thatassumed the presence of eye bearing individuals.

Method 2400 may include executing within a single frame-time of thesequence: selectively controlling subsequent emissions to different FOVsegments having power levels that differ from one another by at least afactor of 2 or more (e.g., a subsequent emission to one FOV segment mayhave a power level at least twice as high as the subsequent emission toanother segment, in the same frame-time), based on the correspondingpreliminary-detection information. A depth-map for this frame-time maybe generated (e.g. in stage 580). This may allow, for example, high SNR,or long distance detection, in some parts of the FOV, while maintainingeye safety compliance in other regions of the FOV or even across theentire FOV (e.g., in view of accumulated energy thresholds).

In some embodiments, stage 2450 may include selectively controlling thesubsequent emission to prevent saturation of a detection path by whichthe sensor detection information is obtained. This may include thesensor, or any component of the LIDAR in the detection and/or processingpath—e.g. amplifier, analog-to-digital converter, etc. The prevention ofsaturation may be leveraged in advanced processing of the detectionresults (e.g. for estimating reflectivity level of a detected target).

Method 2400 may include limiting (or otherwise managing) the emissionlevels to a given FOV segment in a given frame-time based on detectionresults in a preceding frame (or frames)—either of the same segment orof other segments. Method 2400 may include limiting (or otherwisemanaging) the emission levels to a given segment in a given frame-timebased on detection results of another segment (either in the sameframe-time, or in preceding frame-time).

Method 2400 may include controlling subsequent emissions to a segment ofthe FOV (e.g. in the same frame-time), based on preliminarydetection-information of the same FOV segment or another segment of theFOV which was obtained in the same frame-time. For example, detection ina particular FOV segment of a target, especially one corresponding to aneye bearing individual, within an immediate area of the LIDAR may affectsubsequent light emissions provided to the same FOV segment and orprovided to one or more surrounding FOV segments. Such targets, forexample, may span two or more FOV segments or may be expected to move toneighboring FOV segments.

Method 2400 may include selectively controlling preliminary emission toa particular FOV segment, prior to the obtaining of the preliminarydetection-information, based on detection-information collected during aprevious frame-time. In some embodiments different light sources may beused for the preliminary illumination and for the subsequentillumination. For example—while the subsequent emission may be projectedby the main light source of the LIDAR, the preliminary illumination maybe projected by another light source (e.g. visible light source, or evena light source of another system). Optionally, the preliminary detectioninformation is based on detection of at least one photon emitted by atleast one light source of the LIDAR which is not projecting during therespective subsequent emission. The different light sources may becontrolled by a single light-source controller, or by differentcontrollers.

The detection of the preliminary detection-information and of thesubsequent detection-information may be executed by different sensors.For example, the preliminary detection information may be based ondetection by least one sensor optimized for close range detection, whilemethod 2400 also includes processing detection information of reflectedphotons of the subsequent emission detected by at least one other sensoroptimized for larger range detection. The use of sensors of differenttypes may be combined with use of light sources of different types (e.g.optimized for the different sensors or vice versa), but this is notnecessarily so. In one example, sensor 116 may include an AvalanchePhoto Diode (APD) detector for close range objects detection in additionto (or alternatively to) the array of Single Photon Avalanche Diodes(SPADs).

A preliminary illumination of an FOV segment may be used in somesegments of the FOV (e.g. if the preliminary illumination is below athreshold level—e.g. eye safety threshold). Illumination to othersegments of the FOV (e.g. with energy level exceeding the thresholdlevel) may be governed by analysis of the preliminarydetection-information of the relevant frames. For example—thecircumference of the FOV may be analyzed using preliminary low levelinvestigatory signals, while the center of the FOV may be scanned usinghigher power light projections, if the regions of the FOV around thecircumference of the FOV return an indication of low risk to eye bearingindividuals.

Method 2400 may include executing within a frame-time of the FOV scansteps including, e.g., obtaining circumference detection-informationbased on light emitted by the LIDAR during the frame-time and reflectedfrom one or more objects in at least one segment located at acircumference of the FOV. The steps may also include selectivelycontrolling light emission to segments located at a center of the FOVbased on the circumference detection-information.

Referring to method 2400 as a whole, and to any variation of which isdiscussed above, it is noted that method 2400 may be embodied into acomputer readable code (a set of instructions) which can be executed bya processor (e.g. a controller of a LIDAR). A non-transitorycomputer-readable medium for controlling operation of a Light Detectionand Ranging device (LIDAR) which generates a sequence of depth maps ishereby disclosed (each depth map of the sequence being generated in acorresponding subsecond frame-time). That non-transitorycomputer-readable medium may include instructions stored thereon, thatwhen executed on a processor, may perform steps including: (a) obtainingpreliminary detection-information of light emitted by the LIDAR duringthe respective frame-time and reflected from the respective segment; and(b) selectively controlling, based on the preliminarydetection-information, subsequent emission of light by the LIDAR to therespective segment during the respective frame-time. Any other step ofmethod 2400 may also be implemented as instructions stored on thecomputer-readable medium and executable by the processor.

FIG. 25A is a flow chart illustrating an example of method 2500, inaccordance with the presently disclosed subject matter. Method 2500 isone possible implementation of method 2400. As exemplified in FIG. 25A,optionally the selective control of further emission of light by theLIDAR (in a given segment in a given frame-time) based on detectionresults from the same frame-time can be repeated several times in thesafe frame-time. For example, this sequence of emitting, detecting,analyzing and selective controlling may be repeated with respect to eachpulse emitted relative to a particular FOV segment.

Method 2500 may include, in some embodiments, steps for detecting anobject within a range threshold of the LIDAR and setting the subsequentlight emission based on whether or not an object has been detected.LIDAR system 100, or the LIDAR as described above with reference to FIG.23, may control one or more light sources 112 to emit a light pulsetoward the immediate area. The light pulse may be directed toward aparticular segment of the FOV by one or more deflectors 114. If anobject is within the particular segment of the FOV, the LIDAR system 100may receive light reflected from that object via one or more sensors 116or a sensor array. A processor 118 or range estimator 2390 may use thereflected light to determine the distance between the object and theLIDAR system 100. If the object is within a threshold distance,processor 118 may regulate at least one of the light sources 112 and atleast one of the light deflectors 114 to prevent an accumulated energydensity of the light projected in the immediate area to exceed a maximumpermissible exposure. If no object is detected, a subsequent pulse oflight may be emitted in the same segment to detect if there is an objectbeyond the immediate area.

For example, if a pedestrian is detected, then subsequent light emissioncharacteristics may be determined to account for the presence of thepedestrian. In some embodiments, light emissions to a particular FOVsegment or segments in which the pedestrian is determined to reside maybe limited to power levels, aggregated energy levels, time durations,etc. to comply with applicable eye safety regulations. Advantages ofthis embodiment include increased safety to pedestrians or other peoplein the area of the LIDAR by reducing the emission power to within arange deemed safe by local or federal regulations.

FIG. 25B illustrates an example method 2500) for detecting objects.Method 2500 may be performed by at least one processor (e.g., processor118 of processing unit 108 of LIDAR system 100 as depicted in FIG. 1Aand/or two processors 118 of processing unit 108 of the LIDAR systemdepicted in FIG. 2A). At step 2502, processor 118 controls at least onelight source (e.g., light source 112 of FIG. 1A, laser diode 202 oflight source 112 of FIG. 2A, and/or plurality of light sources 102 ofFIG. 2B) in a manner enabling light flux of light from at least onelight source to vary over a scanning cycle of a field of view (e.g.,field of view 120 of FIGS. 1A and 2A). For example, processor 118 mayvary the timing of pulses from the at least one light source.Alternatively or concurrently, processor 118 may vary the length ofpulses from the at least one light source. By way of further example,processor 118 may alternatively or concurrently vary a size (e.g.,length or width or otherwise alter a cross-sectional area) of pulsesfrom the at least one light source. In a yet further example, processor118 may alternatively or concurrently vary the amplitude and/orfrequency of pulses from the at least one light source.

Step 2504 may further include processor 118 controlling at least onedeflector (e.g., light deflector 114 of FIG. 1A, deflector 114A and/ordeflector 114B of FIG. 2A, and/or one-way deflector 214 of FIG. 2B) todeflect light from the at least one light source in order to scan thefield of view. For example, processor 118 may cause mechanical movementof the at least one light deflector to scan the field of view.Alternatively or concurrently, processor 118 may induce a piezoelectricor thermoelectrical change in the at least one deflector to scan thefield of view.

At step 2506, processor 118 may receive from at least one sensor (e.g.,sensor 116 of FIG. 1A), reflections signals indicative of lightreflected from objects in the field of view. In one embodiment, thereflections signals may be associated with a single portion of the fieldof view (e.g., second FOV 414 of FIG. 4B). At step 2508, processor 118may determine, based on the reflections signals of an initial lightemission, whether an object is located in an immediate area of the fieldof view within a threshold distance from the at least one lightdeflector. Consistent with one embodiment, the threshold distance may beassociated with an ocular hazard distance. In other words, processor 118may determine if the amount of light projected may damage an individuallocated in the immediate area. Consistent with another embodiment, thethreshold distance may be associated with a sensor saturation distance.In other words, processor 118 may determine if the amount of lightprojected may cause the reflected light to overflow sensor 116.

When no object is detected in the immediate area, i.e., at step 2510,processor 118 may control the at least one light source such that anadditional light emission is projected toward the immediate area,thereby enabling detection of objects beyond the immediate area.Additionally, when an object is detected in the immediate area, i.e., atstep 2512, processor 118 may include regulating at least one of the atleast one light source and the at least one light deflector to preventan accumulated energy density of the light in the immediate area toexceed a maximum permissible exposure. In accordance with the twoembodiments described above, the maximum permissible exposure may beassociated with the amount of light projected that may damage anindividual located in the immediate area, or the amount of lightprojected that may cause the reflected light to overflow sensor 116 suchthat it may damage its functionally.

Parallel Scene Scanning in Lidar Using a Common Steerable Deflector

In a LIDAR system consistent with embodiments of the present disclosure,a plurality of light sources may be used. For example, using a pluralityof light sources may allow for concurrent scanning of different portionsof a field of view and/or for scanning of the field of view using lightof differing wavelength, intensity, etc. Furthermore, a LIDAR systemconsistent with embodiments of the present disclosure may use a commondeflector to aim light from the plurality of light sources. For example,a LIDAR system consistent with embodiments of the present disclosure mayconcurrently aim light from the plurality of light sources towarddifferent directions in the FOV using a single deflector. By using acommon deflector, the size, cost, and/or complexity of the LIDAR systemmay be reduced. In some embodiments, a LIDAR system consistent withembodiments of the present disclosure may use the same deflector to aimlight from the plurality of light sources and to aim reflectionsreceived from the field of view. In some embodiments, a light source ofthe plurality of light sources may include a plurality of individuallight sources which operate in unison (e.g., in order to increase flux,etc.). Such a plurality may include similar individual light sources butmay also include individual light sources of different kinds and/or withdiffering properties.

FIGS. 26A, 26B, and 26C illustrate methods 2600, 2630, and 2660(respectively), for detecting objects using LIDAR (in particular—onewith a common deflector), in accordance with examples of the presentlydisclosed subject matter. Any one of methods 2600, 2630 and 2660 may beperformed by at least one processor (e.g., processor 118 of processingunit 108 of LIDAR system 100 as depicted in FIG. 1A, two processors 118of processing unit 108 of the LIDAR system depicted in FIG. 2A, at leastone processor 2702 of LIDAR system 2700 of FIG. 27, and/or at least oneprocessor 2802 of LIDAR system 2800 of FIG. 28). The at least oneprocessor may be located within the body of a vehicle (e.g., vehicle4201 of FIG. 42A, vehicle 4205 of FIG. 42B, vehicle 4209 of FIG. 42C, orthe like, as described below). Any combination of methods 2600, 2630,and/or 2660 may also be implemented by the at least one processor. Suchcombinations may include any combination of two or more steps from anyof methods 2600, 2630, and/or 2660, discussed below. Furthermore,methods 2600, 2630, and/or 2660 may optionally be executed by any LIDARsystem consistent with the disclosed embodiments. Any discussionpertaining to the components of the LIDAR system in the context of anyone of these methods (2600, 2630, and 2660) is also applicable in anon-limiting way, mutatis mutandis, for the other two methods.

At step 2601, at least one processor 118 or 2702 or 2802 controls atleast one deflector (e.g., deflector 2704 of LIDAR system 2700 of FIG.27 and/or deflector 2804 of LIDAR system 2800 of FIG. 28) to deflectlight from a plurality of light sources (e.g., light sources 2706, 2708,and 2710 of LIDAR system 2700 of FIG. 27 and/or light sources 2806 and2808 of LIDAR system 2800 of FIG. 28) along a plurality of outboundpaths, towards a plurality of regions (e.g., regions 2712 a, 2712 b, and2712 c of FIG. 27 and/or regions 2810 a and 2810 b of FIG. 28) forming afield of view (e.g., field of view 2712 of FIG. 27 and/or field of view2810 of FIG. 28) while the at least one deflector is in a particularinstantaneous position. For example, at each instantaneous position ofthe at least one deflector, the light of each of the different lightsources may be directed to a portion of the corresponding region as, forexample, depicted in FIGS. 2B, 27, and 28. The aforementioned pluralityof regions (e.g., 2712 a, 2712 b) may form the field of view by spanningover a larger field of view that is larger than any of the respectiveregions. In some embodiments, the formed FOV may be continuous (e.g., asexemplified in FIGS. 27 and 28). Alternatively or concurrently, theformed FOV may include two or more separated FOV regions.

One or more properties of the plurality of light sources may vary. Forexample, as explained below, the wavelength of emitted light from atleast two of the plurality of light sources may differ. By way offurther example, the max power, duty cycle, pulse timing, pulse length,or the like of at least two of the plurality of light sources maydiffer. On the other hand, one or more properties of the plurality oflight sources may be the same or at least substantially similar betweenthe light sources.

For example, the plurality of light sources may include at least threeseparate light sources, as depicted in FIG. 27. In some embodiments, theangles between light from the plurality of light sources may be fixedthroughout the scanning. For example, light from a first light sourcemay impinge on a surface of the deflector at angle α₁(t) at differenttimes t, and light from a second light source may impinge on the samesurface of the deflector at angle α₂(t) at the different times t, andα₁(t)−α₂(t) may be constant for all different times t. In embodimentswhere the light sources are not arranged on a single plane, two anglesmay be used to identify the incidence angle of each light source on thesurface of the deflector. In some embodiments, each light source may begenerally associated with a differing region of the field of view. Forexample, at least a first region of the field of view (e.g., region 2712a of FIG. 27) may be adjacent to at least a second region (e.g., region2712 b of FIG. 27) and spaced from at least a third region (e.g., region2712 c of FIG. 27). Alternatively or concurrently, in such an example,at least each region of the field of view may be associated with adiffering angular portion of the field of view. In some embodiments, thedifferent regions may be of similar size (e.g., similar angular size orthe like), which may be defined, for example, by the range ofinstantaneous positions of the respective deflector 114 of FIG. 1A.

In some embodiments, the at least one deflector may include a singledeflector configured to pivot along two separate axes, as depicted inFIGS. 27 and 28. Accordingly, the single deflector may steer and/ordeflect light along the two separate axis. Alternatively orconcurrently, the at least one deflector may include a deflector arraywith a plurality of deflectors configured to pivot individually, asdepicted in FIG. 3B. As used herein, the term “pivot” may refer to amechanical movement of the deflector or of reflectors within thedeflector but may also refer to any other way of moving betweendiffering instantaneous positions, as discussed in greater detail withrespect to deflector 114 of FIG. 1A (e.g., with respect to OPAs, VCSELarrays. MEMS arrays, or the like).

In certain aspects, during a scanning cycle, the at least one lightdeflector may be located in a plurality of different instantaneouspositions. For example, the at least one light deflector may be moved ina continuous sweeping motion between different instantaneous positions.Alternatively, the at least one light deflector may be moved during thescanning cycle between a plurality of discreet instantaneous positionsrather than being moved in a continuous sweep.

In some embodiments, the at least one deflector may be two-dimensionaland thus define two axes. In such embodiments, the regions of the fieldof view may be arranged over one axis of the at least one deflector, orover both. Alternatively or concurrently, two, three, or more regions ofthe FOV may be arranged along a straight line, parallel to each other,e.g., each covering substantially the same area. Accordingly, scanningwithin a scanning cycle may occur in parallel in another (substantiallyperpendicular) direction to the at least one axis.

In some embodiments, the at least one light deflector may be containedwithin the same housing as at least one of the plurality of lightsources. In other embodiments, the at least one light deflector may becontained within a housing separate from the plurality of light sources.

At step 2603, at least one processor 118 or 2702 or 2802 controls the atleast one deflector such that, while the at least one deflector is inthe particular instantaneous position, light reflections from the fieldof view are received on at least one common area (e.g., common area 2714of deflector 2704 of FIG. 27, common area 2748 of FIG. 27, and/or commonarea 2812 of deflector 2804 of FIG. 28) of the at least one deflector.In certain aspects, in the at least one common area, at least some ofthe light reflections of at least some of the plurality of light sourcesimpinge on one another. For example, the area on which one lightreflection is received may overlap, at least in part, with the area onwhich another light reflection is received. Such impinging may besimultaneous or may occur at differing times. For example, lightreflections traveling from differing distances may arrive at distincttimes. By way of further example, light from the plurality of lightsources may be emitted at different timings, thereby generatingreflections at different times. Such timing may vary across theplurality of light sources.

At step 2605, at least one processor 118 or 2702 or 2802 receives, fromeach of a plurality of detectors (e.g., detectors of sensors 2716, 2718,and 2720 of FIG. 27 and/or detectors of sensor 2814 of FIG. 28), atleast one signal indicative of light reflections from the at least onecommon area while the at least one deflector is in the particularinstantaneous position. For example, the plurality of detectors mayabsorb the light reflections and convert the absorbed reflections to anelectric signal, to a digital signal, etc., for sending to at least oneprocessor 118 or 2702 or 2802. Accordingly, the plurality of detectorsmay comprise any photosensitive devices capable of measuring properties(e.g., power, frequency) of electromagnetic waves and generating anoutput (e.g., a digital signal) relating to the measured properties. Incertain aspects, the received light reflections may be from the commonimpingement area, that is, from the area in which the reflections fromtwo or more light sources strike, as explained above.

In some embodiments, the plurality of detectors may be part of a singlesensor configured to measure at least two differing distances associatedwith a particular position of the at least one light deflector, e.g., asdepicted in FIG. 28. For example, the at least two differing distancesmay be associated with at different parts of the FOV. Alternatively orconcurrently, the at least two differing distances may be determined inthe same pixel. e.g., by photons reflected from different targets partlyhiding each other. In other embodiments, the plurality of detector maybe part of different sensors separated from one another and located indifferent locations within the LIDAR system.

In examples where the plurality of light sources include at least threeseparate light sources (and in some in which the plurality of lightsources includes two light sources), each light source may be associatedwith a differing region of the field of view, and at least a firstregion of the field of view may be located adjacent at least a secondregion and spaced from at least a third region, the plurality ofdetectors may be associated with at least three separate sensors (ortwo, for examples with two light sources). In such embodiments, each ofthe at least three separate sensors may be associated with a differinglight source, e.g., as depicted in FIG. 27. Furthermore, in suchembodiments, the plurality of detectors may be configured toconcurrently detect a first object located in the first region of thefield of view and a second object located in the third region of thefield of view. Such detection may be concurrent, for example, within thescanning time of one of the pixels of the first region. However, suchconcurrence may not be instantaneously concurrent. For example, asexplained above light reflections traveling from differing distances mayarrive at distinct times. By way of further example, light from theplurality of light sources may be emitted at different timings, therebygenerating reflections at different times.

Method 2600 may include additional steps. For example, method 2600 mayfurther include scanning the field of view by repeatedly moving the atleast one deflector, as explained above. During a single scanning cycleof the field of view, the at least one deflector may be located in aplurality of different instantaneous positions (at different times).Accordingly, in different instantaneous positions the deflection oflight from the plurality of light sources and/or of reflections may alsobe different. Accordingly, the light may be directed at and/or thereflections may be received from different regions of the field of view.

By way of further example, method 2600 may include determining, based onthe light reflections from the at least one common area, a plurality ofdistance measurements associated with differing regions of the field ofview. For example, one distance measurement may be to a first vehicle ina first region, and another distance measurement may be to a secondvehicle in a second region. By way of further example, one distancemeasurement may be to a vehicle in a first region, and another distancemeasurement may be to a road in a second region (which may, for example,be behind, ahead of, or next to the vehicle). By way of yet a furtherexample, one distance measurement may be to a first vehicle in a firstregion, and another distance measurement may be to an object in a secondregion (which may, for example, be on the side of a road). In certainaspects, some objects may be detected in different regions, e.g.,because the regions partly overlap and/or because the object is locatedon a border between those two regions.

Method 2600 may further include controlling the plurality of lightsources so that a first light source emits more light flux toward the atleast one deflector than a second light source at a first instantaneousposition of the at least one deflector (i.e., while the at least onedeflector remains in the first instantaneous position), and the secondlight source emits more light flux toward the at least one deflectorthan the first light source at a second instantaneous position of the atleast one deflector. By way of example, at least one processor 118 or2702 or 2802 may increase the light flux from a first light source at afirst instantaneous position when the light from the first light sourceis directed straight ahead and may increase the light flux from a secondlight source at a second instantaneous position when the light from thesecond light source is directed straight ahead. Accordingly, more energymay be expended viewing objects directly ahead than objects to the side.As explained above, at least one processor 118 or 2702 or 2802 may varythe timing of pulses from the plurality of light sources, vary thelength of pulses from the plurality of light sources, vary a size (e.g.,length or width or otherwise alter a cross-sectional area) of pulsesfrom the plurality of light sources, vary the amplitude and/or frequencyof pulses from the plurality of light sources, and/or change parametersof a continuous wave (CW) or quasi-CW light emission (e.g., itsamplitude, its modulation, its phase, or the like) from the plurality oflight sources. In some embodiments, flux management in the differentregions (by the different light sources) may be managed independently ofthe other regions. Alternatively or concurrently, at least one processor118 or 2702 or 2802 may balance between the optical budget and/or powerbudget of two or more regions together (e.g., in order not to exceed amaximal power consumption).

Referring to method 2630 which is illustrated in FIG. 26B, at step 2631,at least one processor 118 or 2702 or 2802 moves at least one deflectorto deflect light from a plurality of light sources along a plurality ofoutbound paths, towards a plurality of regions forming a field of viewwhile the at least one deflector is in a particular instantaneousposition. The term “move” should be construed broadly, as discussed ingreater detail and with several examples above. For example, at eachinstantaneous position of the at least one deflector, the light of eachof the different light sources may be directed to a portion of thecorresponding region as, for example, depicted in FIGS. 2B, 27, and 28.

One or more properties of the plurality of light sources may vary, asexplained above with reference to method 2600 of FIG. 26A. In addition,as with method 2600 of FIG. 26A, the plurality of light sources mayinclude at least two (e.g., as depicted in FIG. 28), at least three(e.g., as depicted in FIG. 27), or more separate light sources. In suchan example, each light source may be generally associated with adiffering region of the field of view. Alternatively or concurrently,the regions may at least partly overlap (e.g., in order to improveperformance, to increase maximal flux in that area, to calibrate betweentwo areas, to allow for backup in case of failure in important parts ofthe FOV, when operating in different wavelengths, etc.). Furthermore, insuch an example, at least a first region of the field of view may beadjacent at least a second region and spaced from at least a thirdregion. Alternatively or concurrently, in such an example, at least eachregion of the field of view may be associated with a differing angularportion of the field of view.

In some embodiments, as with method 2600 of FIG. 26A, the at least onelight deflector may be contained within the same housing as at least oneof the plurality of light sources. In other embodiments, the at leastone light deflector may be contained within a housing separate from theplurality of light sources.

At step 2633, while the at least one deflector is in the particularinstantaneous position, the at least one deflector may receive, on atleast one common area of the at least one deflector, light reflectionsof the plurality of light sources from objects in the field of view. Incertain aspects, in the at least one common area, at least some of thelight reflections impinge on one another. For example, as explainedabove with reference to method 2600 of FIG. 26A, the area on which onelight reflection is received may overlap, at least in part, with thearea on which another light reflection is received. Such impinging maybe simultaneous or may occur at differing times. For example, lightreflections traveling from differing distances may arrive at distincttimes. By way of further example, light from the plurality of lightsources may be emitted at different timings, thereby generatingreflections at different times. Such timing may vary across theplurality of light sources.

At step 2635, each of a plurality of detectors (e.g., detectors ofsensors 2716, 2718, and 2720 of FIG. 27 and/or detectors of sensor 2814of FIG. 28) may receive light reflections from the at least one commonarea when the at least one light deflector is in the instantaneousposition. For example, as explained above with reference to method 2600of FIG. 26A, the plurality of detectors may comprise any photosensitivedevices capable of measuring properties (e.g., power, frequency) ofelectromagnetic waves and generating an output (e.g., a digital signal)relating to the measured properties. In certain aspects, the receivedlight reflections may be from the common impingement area, that is, fromthe area in which the reflections from two or more light sources strike,as explained above.

In some embodiments, as with method 2600 of FIG. 26A, the plurality ofdetectors may be part of a single sensor configured to measure at leasttwo differing distances associated with a particular position of the atleast one light deflector, as depicted in FIG. 28. For example, the atleast two differing distances may be associated with at different partsof the FOV. Alternatively or concurrently, the at least two differingdistances may be determined in the same pixel, e.g., by photonsreflected from different targets partly hiding each other.

Method 2630 may include additional steps, such as (though not limitedto) any combination of one or more steps discussed with respect tomethod 2600.

Referring to method 2660 which is illustrated in FIG. 26C, at step 2661,at least one processor 118 or 2702 or 2802 controls a plurality of lightsources aimed at least one deflector. For example, as with step 2601 ofmethod 2600, at least one processor 118 or 2702 or 2802 may control thetiming of pulses from the plurality of light sources, control the lengthof pulses from the plurality of light sources, control a size (e.g.,length or width or otherwise alter a cross-sectional area) of pulsesfrom the plurality of light sources, control the amplitude and/orfrequency of pulses from the plurality of light sources, and/or controlparameters of a continuous wave (CW) or quasi-CW light emission (e.g.,its amplitude, its modulation, its phase, or the like) from theplurality of light sources.

At step 2663, at least one processor 118 or 2702 or 2802 receives datafrom a plurality of detectors configured to detect reflections from theplurality of light sources. In some embodiments, as with method 2600 ofFIG. 26A, the plurality of detectors may be part of a single sensorconfigured to measure at least two differing distances associated with aparticular position of the at least one light deflector, as depicted inFIG. 28. For example, the at least two differing distances may beassociated with at different parts of the FOV. Alternatively orconcurrently, the at least two differing distances may be determined inthe same pixel, e.g., by photons reflected from different targets partlyhiding each other.

At step 2665, at least one processor 118 or 2702 or 2802 moves the atleast one deflector to deflect light from the plurality of light sourcesalong a plurality of outbound paths towards a plurality of regionsforming a field of view while the at least one deflector is in aparticular instantaneous position. The term “move” should be construedbroadly, as discussed in greater detail and with several examples above.

As with method 2600 of FIG. 26A, the plurality of light sources mayinclude at least three separate light sources, as depicted in FIG. 27.In such an example, each light source may be generally associated with adiffering region of the field of view. Furthermore, in such an example,at least a first region of the field of view may be adjacent at least asecond region and spaced from at least a third region. Alternatively orconcurrently, in such an example, at least each region of the field ofview may be associated with a differing angular portion of the field ofview.

At step 2667, at least one processor 118 or 2702 or 2802 controls the atleast one deflector such that while the at least one deflector is in theparticular instantaneous position, light reflections from the field ofview are received on at least one common area of the at least onedeflector. In certain aspects, in the at least one common area, at leastsome of the light reflections of at least some of the plurality of lightsources may impinge on one another. Illustrative examples are providedabove with reference to method 2600 of FIG. 26A.

At step 2669, at least one processor 118 or 2702 or 2802 receives, fromeach of a plurality of detectors, at least one signal indicative oflight reflections from the at least one common area while the at leastone deflector is in the particular instantaneous position. Illustrativeexamples are provided above with reference to method 2600 of FIG. 26A.

Method 2660 may include additional steps, such as (though not limitedto) any combination of one or more steps discussed with respect tomethods 2600 and/or 2630.

By way of further example, as with method 2600 of FIG. 26A, method 2660may include determining, based on the light reflections from the atleast one common area, a plurality of distance measurements associatedwith differing regions of the field of view. Method 2660, similar tomethod 2600 of FIG. 26A, may further include controlling the pluralityof light sources so that a first light source emits more light fluxtoward the at least one deflector than a second light source at a firstinstantaneous position of the at least one deflector, and the secondlight source emits more light flux toward the at least one deflectorthan the first light source at a second instantaneous position of the atleast one deflector.

Although described as using fully separate regions forming a field ofview, methods 2600, 2630, and/or 2660 may be implemented with at leastone pair of partly overlapping FOV regions. This may be implemented fordifferent uses, such as (although not limited to): in order to improveperformance, to increase maximal flux in that area, to calibrate betweentwo or more areas, to allow for backup in case of failure in importantparts of the FOV, when operating in different wavelengths, etc. Some ofthese uses are discussed in further detail below.

In embodiments where the plurality of light sources may include at leasttwo separate light sources, each light source may be configured toproject light at a differing wavelength (e.g. the light sources of FIGS.27 and 28). A light source which operates in a given wavelength may emitlight in a wavelengths band, which may be a narrow band (for example, alight source having a wavelength of 600 nm may emit light innon-negligible amounts within a bandwidth of ±2 nm, i.e., between598-602 nm). In certain aspects, a light source of LIDAR systems 100,200, 2700, and/or 2800 may be coupled with a filter, e.g., in order tolimit the range of projected light wavelengths. In some embodiments, atleast a first light source may configured to project light at awavelength between 400-800 nm and/or between 800-1000 nm and at least asecond light source is configured to emit light in a wavelength greaterthan 800 nm (or 850 nm or 900 nm, etc.) and/or greater than 1500 nm. Incertain aspects, the first light source may be configured to projectlight at a wavelength such that light from the first light source andlight from the second light source are both completely beyond visiblerange.

In such embodiments, the at least two light sources may be configured toproject light in substantially overlapping regions of the field of view.The use of differing wavelengths in substantially overlapping regionsmay allow for the detection of objects with one wavelength that were notvisible (or at least not as visible) with another wavelength.

In addition, in embodiments where the plurality of light sources may beconfigured to project light at the same (or substantially the same)wavelength, the plurality of light sources may still be configured toproject light in substantially overlapping regions of the field of view.This overlapping may allow for the alignment of results such that errorsin calibration or detection may be reduced and/or that noise from onelight source may be lessened when using a second light source. Moreover,such overlapping may allow for detection of faulty equipment, such asfaulty light sources, detectors, or the like.

Although described as using fully separate light sources, the pluralityof light sources used in methods 2600, 2630, and/or 2660 may comprise asingle light source coupled with beam splitters. Accordingly, the beamsplitters may project beam of light onto the at least one deflector fromdifferent directions, thereby functioning like fully separate lightsources.

FIG. 27 is a diagram illustrating an example LIDAR system 2700 having aplurality of light sources and a common deflector. As depicted in FIG.27, light from the plurality of light sources may impinge on anoverlapping area of the at least one light deflector. Additionally oralternatively, light originating from the plurality of light sources andreflected back from the scene may impinge on an overlapping area of theat least one light deflector. As depicted in FIG. 27, system 2700 atleast one processor 2702 that controls at least one deflector 2704. Atleast one deflector 2704 may be in a particular instantaneous positionduring a scan cycle. At least one processor 2702 may further control aplurality of light sources (e.g., light sources 2706, 2708, and 2710).

The plurality of light sources 2706, 2708, and 2710 may be directedtoward field of view 2712. As depicted in FIG. 27, field of view 2712includes a first region 2712 a adjacent a second region 2712 b andspaced from a third region 2712 c. Although depicted as nonoverlappingin FIG. 27, some embodiments may include two or more regions withsubstantially overlapping areas.

The insert of FIG. 27 depicts a surface of deflector 2704 (e.g., asingle rectangular mirror) and the illumination of light beams fromthree light sources 2706, 2708 and 2710 impinging on surface—illustratedas light beam cross sections 2742, 2744 and 2746. The different shadinglevels represent the accumulated illumination level of each area ofdeflector 2704—illuminated by a single light source, illuminated by twolight sources or illuminated by three light sources (e.g., area 2748).As depicted in the insert, in area 2748, light from three light sources2706, 2708 and 2710 impinge on a common area of the deflector (possibly,but not necessarily, concurrently). As further depicted in the insert,some light from one or more of light sources 2706, 2708 and 2710 may notstrike the deflector (as represented by the dashed ellipses). Forexample, a light beam may exceed the dimensions of the surface (asdepicted in the vertical axis) and thus may also be smaller than thecorresponding dimension of the surface. The insert further depicts thatlight beams 2742, 2744 and 2746 may differ in size and/or may be atleast partly misaligned to one another. In some embodiments, because thereflection wave front may be much larger than an optical opening of theLIDAR system (e.g., system 2700), deflector 2704 may be sized and/orpositioned such that light reflected from a plurality of light sourcesimpinges on the entire active deflective area of the deflector.

In the embodiment of FIG. 27, at least one deflector 2704 has a commonarea 2714. The plurality of light sources 2706, 2708, and 2710 may beaimed at common area 2714. Thus, plurality of light sources 2706, 2708,and 2710 may emit a corresponding plurality of light beams alongoutbound paths (e.g., paths 2722 a, 2722 b, and 2722 c) towards regions2712 a, 2712 b, and 2712 c. The plurality of light beams may cause aplurality of corresponding reflections traveling along return paths(e.g., paths 2724 a, 2724 b, and 2724 c) from field of view 2712 (orfrom objects therein). As further depicted in the example of FIG. 27,each reflection may be directed to a corresponding sensor (e.g., sensors2716, 2718, and 2720) using common area 2714 of at least one deflector2704. As depicted in the example of FIG. 27, none of outbound paths 2722a, 2722 b, and 2722 c are coincident and none of return paths 2724 a,2724 b, and 2724 c are coincident. In other embodiments, at least twooutbound paths and/or at least two return paths may be coincident.

FIG. 28 is a diagram illustrating another example LIDAR system 2800having a plurality of light sources and a common deflector. As depictedin FIG. 28, light from the plurality of light sources may impinge on anoverlapping area of the at least one light deflector. Additionally oralternatively, light originating from the plurality of light sources andreflected back from the scene may impinge on an overlapping area of theat least one light deflector. As depicted in FIG. 28, system 2800 atleast one processor 2802 that controls at least one deflector 2804. Atleast one deflector 2804 may be in a particular instantaneous positionduring a scan cycle. At least one processor 2802 may further control aplurality of light sources (e.g., light sources 2806 and 2808). In theexample of FIG. 28, light sources 2806 and 2808 may have differentwavelengths. In other embodiments, light sources 2806 and 2808 may havedifferent max power, duty cycle, pulse timing, pulse length, or thelike.

Light sources 2806 and 2808 may be directed toward field of view 2810.As depicted in FIG. 28, field of view 2810 includes a first region 2810a and a second region 2810 b. Although depicted as nonoverlapping inFIG. 28, some embodiments may include two or more regions withsubstantially overlapping areas.

In the embodiment of FIG. 28, at least one deflector 2804 has a commonarea 2812. Light sources 2806 and 2808 may be aimed at common area 2812.Thus, light sources 2806 and 2808 may emit a corresponding plurality oflight beams along outbound paths (e.g., paths 2816 a and 2816 b) towardsregions 2810 a and 2810 b. The plurality of light beams may cause aplurality of corresponding reflections traveling along return paths(e.g., paths 2818 a and 2818 b) from field of view 2810 (or from objectstherein). As further depicted in the example of FIG. 28, each reflectionmay be directed to a single sensor 2814 using common area 2812 of atleast one deflector 2804. As depicted in the example of FIG. 28, none ofoutbound paths 2816 a and 2816 b are not coincident, but return paths2818 a and 2818 b are coincident. In other embodiments, at least twooutbound paths may be coincident and/or at least two return paths maynot be coincident.

In some examples, the at least one deflector 2704, 2804, 114, or thelike may include an array of deflectors (e.g. an array of pivotingmirrors, such as an array of pivoting piezo-electric mirrors, or thelike), e.g. as illustrated in FIG. 3B. If such an array of deflector isused for both projection and detection (both transmission and receptionpaths), any combination of allocation of the individual deflections fortransmission, reception, and/or bi-directional use may be used. By wayof example, in an array comprising ten mirrors used by three lightsources to illuminate different portions of the FOV, three mirrors maybe used for transmission corresponding to one light source each, and theremaining seven mirrors may be used for reception. Alternatively, one ortwo mirrors may be used for transmission of all of the light sources(e.g., by utilizing overlapping areas of those mirrors, an example ofwhich is depicted in FIG. 27), and all ten mirrors may be used forreception. Any other combination may also be used. In certain aspects,some or all of the individual deflectors of a deflector array may besynchronized to deflect light at substantially the same angles. Incertain aspects, some or all of the individual deflectors of a deflectorarray may be synchronized to deflect light in different directions withfixed angles between them.

Optical Budget Apportionment in Lidar

As described herein, one function of a LIDAR system may be to generatethree-dimensional depth maps of an environment surrounding of the LIDARsystem by projecting light to the environment and then collecting andanalyzing light reflections from objects in the environment. In general,the usefulness of a LIDAR system and its depth maps may increase withthe level of information that can be gleaned from the collected lightand with the resolution of the generated depth maps. But, practicallimitations may exist that may preclude the generation of higherresolution depth maps simply by ramping up the amount of light energyemitted to the environment by the LIDAR system. First, eye safety is aprimary constraint that may limit an amount of light energy that can beoutput by the LIDAR. To ensure eye safety, and to comply with applicableregulations, a LIDAR system may be limited to light projections that donot exceed a certain energy density over a certain time period.Moreover, even if eye safety was not a concern, there may be otherpractical limitations that prohibit unmitigated light emission to theenvironment of the LIDAR. For example, the LIDAR system may have finiteoptical budget and/or computational budget that may limit the LIDARsystem's ability to increase detection resolution simply through blanketincreases in light emissions to the LIDAR FOV. Conceptually, the opticalbudget and computational budget may reflect maximum capabilities of theLIDAR system over a particular period of time in terms of availablelight output power and computing power. The LIDAR system may also beconstrained by technical constrains such as power restrictions,overheating, output of the light sources, etc.

That is not to say, however, that depth maps generated by the LIDARsystem must be restricted to an absolute resolution level over all areasof the LIDAR FOV. Rather, as discussed below and throughout the varioussections of this disclosure, the optical budget and computational budgetof a LIDAR system may be apportioned in such a way that more resources(e.g., more of the optical budget and/or computational budget) may bedevoted to certain areas of the LIDAR FOV than to other areas of theLIDAR FOV. As a result, it may be possible to generate correspondingdepth maps that have high resolution in some areas (e.g., areascorresponding to regions of interest) and lower resolution in otherareas (e.g., regions of lower interest or non-interest). The descriptionbelow and throughout many sections of the present disclosure addressesvarious scenarios, conditions, situations, etc. for which non-uniformapportionment of optical budget and/or computational budget may bedesirable. The description below and throughout also provides examplesfor how the available optical budget and/or computational budget may bedynamically allocated in order to aid in the generation of depth mapspotentially offering increased levels of information in one or moreareas of interest covered by the depth maps.

FIG. 29 provides a block diagram representation of a LIDAR system 100along with various sources of information that LIDAR system 100 may relyupon in apportioning an available optical budget and/or computationalbudget. In some embodiments, LIDAR system 100 may include at least oneprocessor 118 configured to access an optical budget (or any informationindicative of at least one aspect of an optical budget or from which anoptical budget may be derived or determined) stored in memory 2902, theoptical budget being associated with at least one light source 112 anddefining an amount of light that is emittable in a predetermined timeperiod by the at least one light source. Memory 2902 may be associatedwith processing unit 108 of LIDAR system 100, as shown in FIG. 29. Insome embodiments, however, memory 2902 may be associated with a host(e.g., a vehicle, a vehicle-computer) on which LIDAR system 100 isdeployed. For example, in some cases, memory 2902 may be associated withelectronic control unit 2904 of a host vehicle and may be accessible byprocessor 118 over data bus 2900. In other embodiments, memory 2902 maybe associated with a system or systems located remotely with respect toLIDAR system 100 (or its host). For example, in some embodiments, memory2902 may be associated with a remote server (not shown) and may beaccessible, e.g., via cloud 2916 (e.g., an Internet connection) or usinga wireless transceiver 2901.

Processor 118 may also be configured to receive information indicativeof a platform condition for the LIDAR system (e.g., from any ofinformation sources 2904, 2906, 2908, 2910, 2912, 2914, 2916, 2918,2920, or from any other suitable information source). A platformcondition for the LIDAR system may refer to any operational parameter,parameter value, observed condition, instruction, informational item,etc., relating to one or more aspects of a LIDAR system, the environmentsurrounding the LIDAR system, the host on which the LIDAR system isdeployed, etc. that may justify allocating more light to at least onegroup of LIDAR FOV portions or in one scanning cycle than is provided toanother group of LIDAR FOV portions or in another scanning cycle over aparticular period of time.

While the received information may be obtained from one or more sourcesoutside of LIDAR system 100, information indicative of a platformcondition for the LIDAR system may also include information obtainedfrom sources internal to system 100 (e.g., via one or more components ofthe system, including light projector 112, deflector 114, detector 116,feedback elements, etc.). Based on the received information, processor118 may dynamically apportion the optical budget to a field of view ofLIDAR system 100 using, for example, two or more operational parametersassociated with the light source 112 and/or deflector 114, including,for example, scanning rates, scanning patterns, scanning angles, spatiallight distribution, and/or temporal light distribution. Processor 118may further output signals for controlling light source 112 and/ordeflector 114 in a manner enabling light flux to vary over scanning ofthe field of view of LIDAR system 100 in accordance with the dynamicallyapportioned optical budget.

An optical budget may be expressed relative to any parameter, value, orset of parameters or values related to an amount of light that can beemitted to a LIDAR FOV over a certain time period (e.g., in terms ofLIDAR scanning cycles; time measurements in milliseconds, seconds, etc.,or any other indicator of a time period). In some embodiments, anoptical budget of a LIDAR system may depend on the capabilities of oneor more light sources included in the LIDAR system. For example, anoptical budget of LIDAR system 100 may be associated with light source112 and may define an amount of light that is emittable in apredetermined time period by light source 112. Defining an amount oflight may refer to any parameter or parameter relationship indicative ofan amount of light (e.g., power, luminosity, light flux, intensity,number of photons, number of light pulses, duty cycle, pulse width,pulse amplitude, illumination duration, etc.) relative to some measureof time (e.g., microseconds, milliseconds, seconds, minutes, etc.).

In some cases, an average optical budget for light source 112 may bebetween about 10 milliwatts and 1,000 milliwatts. Additionally oralternatively, an optical budget may reference an amount of lightemittable in a single scanning cycle of the LIDAR FOV. For example, anoptical budget for LIDAR system 100 may be between 10,000 pulses perscanning cycle per light source and 50,000 pulses per scanning cycle perlight source (e.g., for covering 1,000-10,000 beam locations, eachassociated with one or more pixels). In some embodiments, the opticalbudget may be expressed in terms of power available for use by lightsource 112 (e.g., from a vehicle or other host on which LIDAR system 100is deployed). An optical budget may also be defined by an amount oflight that is emittable by light source 112 (or any available lightsources of system 100) in a standard unit of time (e.g., milliseconds,seconds, minutes, etc.).

In some cases, an optical budget may remain fixed. In other cases, anoptical budget stored in memory 2902 may be modified and updated. Suchmodification may occur, for example, based on at least one of anoperational parameter of the LIDAR system and detection informationprovided by the LIDAR system.

Additionally, in some embodiments an optical budget may correspond toonly a single LIDAR system having a single light source. In other cases,an optical budget may refer to a single LIDAR system including aplurality of light sources. In still other cases, an optical budget mayapply to a plurality of LIDAR systems deployed at different locations(e.g., at different locations around a vehicle), each including a singlelight source or a plurality of light sources. In any case, the opticalbudget may define an amount of emittable light available to beapportioned from a plurality of light sources (or plurality of LIDARsystems in the aggregate) in a predetermined time period. Processor 118may dynamically apportion the optical budget of a single LIDARsystem/light source. In other cases, processor 118 may dynamicallyapportion the optical budget associated with multiple lightsources/LIDAR systems.

In addition to an optical budget, LIDAR system 100 (or a combination ofa plurality of LIDAR systems) may have a computational budget that maybe apportioned. The computational budget may refer generally to theprocessing capability of a LIDAR system or systems over a particularperiod of time. The processing capability may depend on the number ofprocessors available (e.g., for controlling the various aspects of theLIDAR system, for receiving and processing detected reflections, forgenerating depth maps, for processing depth map for detecting object andother higher-level and scene-understanding information, and forperforming any other function associated with a LIDAR system or group ofLIDAR systems). The processing capability may depend not only on thenumber of processor available, but may also depend on other parameterssuch as the portion of processing capability of one or more processorsthat is dedicated to certain functions of the LIDAR system (e.g.,generation of the depth maps, controlling scans of the FOV, objectdetection, identification and/or classification, etc.), the processingspeed of one or more available processors, data transfer rates (e.g.,across bus 2900), the number of calculations per unit time that can beperformed by one or more available processors, etc.

While the description below includes details relating to apportionmentof an optical budget, a computational budget may be apportioned inanalogous ways to those described relative to optical budgetapportionment. For example, in some cases a computational budget maypertain an amount of computational resources available to process pointclouds in order to determine what the LIDAR has detected. In some cases,processing relating to the point clouds can require significantcomputing resources—a limited resource. Thus, in some cases, it may bedesirable to determine whether certain areas may be of higherinterest/importance than other areas for processing the associated pointclouds. For example, much of the available processing power may bededicated to processing point clouds and generating depth maps for aregion in front of a vehicle, as that area may have the most importance,especially for a forward moving car. On the other hand, while stillimportant, detections occurring in a field of view extending from theside of a vehicle, in some instances, may have less importance than thefront of a vehicle (unless, for example, the vehicle is turning,stopped, etc.). In such cases, even if grouped detections have beendetected by the LIDAR from reflections signal reflected from a highlyreflective object located 130 meters away from the host vehicle,processor 118 may decide to only process the associated point cloud upto a distance of 40 m (or some distance less than 130 m) from thevehicle to conserve the computational budget (e.g., because it may betoo costly from a computational standpoint to process the full pointcloud including the grouped detections at 130 m, especially if thecomputational expenditure, as in this side-of-the-vehicle example, isnot justified by the importance of the detected objects).

A computational budget may be apportioned not only among available LIDARsystems, such that one LIDAR system may be provided with morecomputation capability than another, for example, through dedication ofthe computational capacity of one or more centralized processors more toone LIDAR system than to another. In another example, the processors oftwo or more LIDAR systems may be aggregated/networked and the aggregateprocessing capabilities may be allocated such that a processor from oneLIDAR system may be dedicated at least in part to computational tasks ofdifferent LIDAR system. For example, the processing capacity from aplurality of available LIDAR systems may be dedicated to computationaltasks associated with a region forward of a host vehicle, a region wherehigh resolution object detection and depth mapping may be desired.

A computational budget may also be apportioned relative to calculationsassociated with a particular LIDAR FOV such that computational tasksassociated with one portion of the FOV may receive more of thecomputation budget than computational tasks associated with anotherportion of the FOV. Some examples of how a computation budget may beapportioned include, for example: detection/clustering (object levelfrom point cloud points); tightening bounding boxes of objects(“bounding boxes”); classification of objects/object type; tracking ofobjects (e.g., between frames); determining object characteristics(e.g., size, direction, velocity, reflectivity, etc.). A computationalbudget may be expressed in terms that relate processing capacity to time(e.g., GMACs, Gflops, power, etc.). It is noted that the budgetapportionment to different parts of the FOV—especially but not onlycomputational budget—may refer to FOV portioning in 3D, and not just in2D. For example, the computational budget may be allocated that for agiven sector of the FOV (e.g. a given 1° by 0.5° sector), 70% of thecomputational budget is allocated for processing detections in rangeswhich exceeds 70 m, 30% of the computational budget is allocated forprocessing detections in ranges closer to the LIDAR than 40 m, and nocomputational budget is allocated for the ranges between 40 and 70 m.

Returning to the optical budget, an available optical budget may beapportioned in any manner enabling more light to be selectively providedto one group of LIDAR FOV portions than to another group of LIDAR FOVportions within a particular time period. In this context, a group ofLIDAR FOV portions may refer to a one or more portions of a particularLIDAR FOV (e.g., one or more pixels, regions, sub-regions, etc. of aparticular LIDAR FOV) or may refer to one or more full LIDAR FOVs (e.g.,where an optical budget may apportioned across multiple LIDAR systems).References to more light may refer to increased light flux, increasedlight density, increased number of photons, etc., e.g., as exemplifiedabove in greater detail.

In some cases, apportionment of the optical budget may be accomplishedthrough variation of a scanning rate associated with a particular LIDARFOV, a scanning pattern, a scanning angle, a spatial light distribution(e.g., providing more light to one or more groups of LIDAR FOV portionsthan to one or more other LIDAR FOV portions), and/or a temporal lightdistribution. Temporal light distribution may involve, e.g., controllingor otherwise changing light flux or an amount of light applied to groupsof LIDAR FOV portions over time such that an overall amount of lightprojected in a first scanning cycle is higher than an overall amount oflight projected in a second subsequent scanning cycle. In some cases,apportionment of an optical budget may be accomplished by varying two ormore of: a scanning rate associated with a particular LIDAR FOV or aparticular LIDAR FOV portion, a scanning pattern, a scanning angle, aspatial light distribution, or a temporal light distribution. Suchvariations may be made with respect to more than one LIDAR FOV, oneLIDAR FOV, a portion of a LIDAR FOV (e.g., a region of interest), onescanning cycle, multiple scanning cycles, etc.

At least part of the dynamic apportionment of the optical budget (e.g.,changing or updating an apportionment based on feedback or otherinformation received relating to at least one platform condition for aLIDAR system) may be performed by determining a scanning rate for one ormore LIDAR systems. For example, at least one processor may beconfigured to determine a scanning rate for at least one of: anear-field portion of a LIDAR FOV, a far-field portion of a field ofview, a narrow-angle sector of a field of view, and/or a wide-anglesector of a field of view.

As noted, optical apportionment may also be accomplished, at least inpart, by determining a scanning pattern for at least one scanning cycleof one or more LIDAR systems. The scanning pattern may be determinedbased on recognition of at least one of the following scenario types:driving on highways, driving off-road, driving in rain, driving in snow,driving in fog, driving in urban areas, driving in rural area, drivingthrough a tunnel, driving in an area close to a predefinedestablishment, turning left, turning right, crossing a lane, approachinga junction, and approaching a crosswalk.

The optical budget apportionment may be accomplished by any suitableprocessor. In some cases, processor 118 of LIDAR system 100 mayapportion an optical budget based on information from one or moresources. Alternatively, or additionally, processors from other LIDARsystems may be used to apportion an optical budget (e.g., an opticalbudget associated with a group of LIDAR systems) and/or one or moreprocessors associated with a LIDAR system host (e.g., a vehicle ECU,etc.) may be used. Any other available processors may also be used toapportion an optical budget.

As noted, optical budget apportionment may result in more light beingapplied to one group of LIDAR FOV portions than to another. Such changesin applied light amounts, for example, may be achieved by varying aratio of optical budget apportionment relative to a first light sourcewithin a plurality of light sources versus an optical budgetapportionment relative to a second light source within the plurality oflight sources (or a similar ratio between LIDAR detectors). Opticalapportionment may also be applied for different reasons relative todifferent LIDAR FOV portions or at different times. For example, in someportions of a LIDAR FOV or at some times during a scanning cycle,optical apportionment may be directed to increasing resolution,detection quality, etc. n a particular FOV portion or in a particulartime period. In other situations, optical apportionment may be directedto increasing detection range associated with a particular FOV portion,a particular FOV sub-region, or in a particular time period. In general,an optical/power budget may be used to achieve different goals inacquiring different frames or different portions of acquired frames.This way a LIDAR system may provide a series of useful or high qualityframes for different ROIs, each being useful for different reasons. Inthis way, the optical budget may be expended in ways determined ashaving a high probability for returning useful information to the hostplatform (e.g., a navigational system of a vehicle).

Regarding controls, any suitable parameter or information element may beused in determining whether and/or how to apportion and optical budget.In some embodiments, a platform condition for the LIDAR system may beused as the basis for optical budget apportionment. As noted above, aplatform condition for a LIDAR system may refer to any operationalparameter, parameter value, observed condition, instruction,informational item, etc., relating to one or more aspects of a LIDARsystem, the environment surrounding the LIDAR system, the host on whichthe LIDAR system is deployed, etc. that may justify providing more lightto at least one group of LIDAR FOV portions or in one scanning cyclethan is provided to another group of LIDAR FOV portions or in anotherscanning cycle over a particular period of time.

Such platform conditions for a LIDAR system may be determined in variousways and using any suitable source of information. In some cases, aplatform condition of a LIDAR system may be determined internal to theLIDAR system. For example, based on acquired light reflections,reflectivity signatures, depth maps, etc., processor 118 may determineone or more characteristics associated with an environment in which theLIDAR system is deployed. In other cases, a platform condition for aLIDAR system (PCLS) may be determined based on information received fromone or more sources separate from LIDAR system 100. For example, asshown in FIG. 29 a PCLS may be determined based on information from oneor more of an electronic control unit 2904 of a host vehicle, one ormore temperature sensors 2906, a GPS receiver 2908, a vehicle navigationsystem 2910, a RADAR unit 2912, one or more other LIDAR systems 2914, anInternet or other network connection 2916, a camera 2920, or any othersuitable source.

In some cases, information indicative of a PCLS may establish one ormore regions of a LIDAR FOV as a region of interest that may justifyhigher proportions of an optical or computational budget as compared toother regions (e.g., regions of less interest or non-interest). A regionof interest may be identified based on a sensed current driving mode ofa vehicle in which the LIDAR system is deployed, which may be determinedbased on one or more outputs of any of information sources 2904, 2906,2908, 2910, 2912, 2914, 2916, 2920, or from LIDAR system 100, or anycombination of these. In one example, a region of interest based on asensed current driving mode may include a one or more portions of aLIDAR FOV overlapping an area that a host vehicle is turning toward (asconveyed by navigation system 2910, GPS receiver 2908, etc.). In anotherexample, a region of interest may correspond to one or more portions ofa LIDAR FOV in which LIDAR system 100 has detected an object, such asanother vehicle, a pedestrian, obstacle, etc. Other examples of regionsof interest and how such regions are identified are included in othersections of this disclosure.

Information indicative of a PCLS on which optical apportionment (orcomputational budget) may be determined may include, among other things,at least one of a vehicle operational parameter, an environmentalcondition, a driving decision, a navigational state of a vehicle, or apower management mode.

Examples of a vehicle operational parameter or a navigational state of avehicle upon which optical apportionment (or computational budget) maybe based may include current speed (e.g., from ECU 2904, GPS 2908), acurrent vehicle heading (e.g., from GPS 2908, navigation system 2910), acurrent braking or accelerating condition (e.g., from GPS 2908, ECU2904), whether the host vehicle is navigating a cross-lane situation(e.g., from navigation system 2908, camera 2920, GPS 2908, etc.).Vehicle operational parameters may also relate to the condition or stateof any components associated with a vehicle platform on which LIDARsystem 100 is deployed or the condition or state of any components ofLIDAR system 100 itself. Such conditions may include a temperature of atleast one component of the LIDAR system, whether a portion of the FOV isblocked (e.g., by rain, mud, debris, etc.), whether a lens is scratched,whether deflector 114 is impeded from reaching certain instantaneouspositions, whether more internal reflections exist at some anglescompared to other angles. A navigational state of the vehicle may alsoinclude a position of the host vehicle relative to three-dimensionalmaps, partial maps, 2-D maps, landmarks, or any combination of map andlandmarks, etc. Maps may be pre-stored, received via a communicationchannel, or generated (e.g. by SLAM).

Examples of an environmental condition may include at least one of aweather condition (e.g., rain, snow, fog, etc. determined based oninformation from camera 2920, cloud 2916, navigation system 2910); alighting condition (e.g., determined based on information from LIDARsystem 100 (ambient light, type of light source, etc.)); anenvironmental temperature (e.g., based on an output from temperaturesensor 2906), and/or a proximity to a predefined type of establishment(e.g., a school as determined based on input from navigation system2910, GPS 2908, camera 2920, etc.). Additional examples of environmentalconditions upon which optical budget (or computational budget)apportionment may be based may include weather conditions, positions ordistribution of detected objects in space (e.g., relative to LIDARsystem 100 and/or a host vehicle), detected characteristics of objectsin space (e.g. shape, reflectivity, characteristics affecting SNR),type/class of objects (e.g., pedestrian, building, vehicle, light post),a relative position of the sun or other light sources, a state oftraffic (e.g., jammed vs. open highway), a state of other host vehiclesystems (e.g., driving related or other sensors—in some cases LIDARsystem 100 may compensate for a malfunctioning camera 2920), conditionsof the road itself (e.g., bumpiness, roughness, going up/down, curving,its reflectivity), map/GPS based data (e.g., road location andorientation in the scene, building location and orientation in scene—(aregion of lower interest may be established relative to a building orother obstacle, as LIDAR may not expect to receive reflections fromobjects on a far side of a building), ambient temperature around LIDARsystem 100, ambient temperature of a host vehicle environment, dataanalysis from previous collected FOV frames (e.g., point clouds, normalto surfaces, reflectivity, confidence levels, etc.). In general, anoptical/power budget may be allocated based on knowledge about theenvironment. For example, GPS data, map data, processed LIDARinformation of previous frames, data from other sensors of the vehicle,or any other source may indicate a presence of a building in a part ofthe FOV, in a given range (e.g. 15 m). While that building may be in aregion of high interest (e.g. directly in front of the vehicle), theprocessor may nevertheless allocate relatively low power to this part ofthe FOV and allocate the surplus energy to other portions of the LIDARFOV, so as not to waste budget on parts of the FOV which are hiddenbehind the building (e.g. beyond 15 m), and cannot be reached,regardless of the amount of light which can be allocated to thatdirection in the FOV.

Examples of a driving decision upon which optical apportionment (orcomputational budget) may be based may include at least one of arural-related indication, an urban-related indication, a current speedof a vehicle containing the LIDAR system, a next driving maneuver, aconditional driving maneuver (a maneuver that may be completed only inthe presence of additional environmental information indicating it issafe to do so), a driving navigation event, a manual-driving indication,and an autonomous-driving indication. Such information may be acquiredbased on outputs provided, for example, by LIDAR system 100 or 2914,navigation system 2910, ECU 2904, GPS 2908, any combinations of thosesources or other potential sources of an indicator of a PCLS.

Examples of a power management mode upon which optical apportionment (orcomputational budget) may be based may include at least one of anindication a normal power operation mode and a power saving mode. Suchinformation may be obtained from ECU 2904, for example, and may reflectan amount of power available from the host vehicle. Other indicators ofa power management mode may be based on a sensed condition of one ormore components of LIDAR system 100 (e.g., whether any components areoverheating or in danger of overheating).

Several examples may further illustrate the collection of a PCLS uponwhich optical or computation budget apportionment may be based. Forexample, during operation, processor 118 may receive input indicative ofa current driving environment of the vehicle. For example, processor 118may receive input that includes at least one of a rural-relatedindication and an urban-related indication. By way of further example,processor 118 may receive input that includes at least one rural-relatedindication, urban-related indication, information associated with alight condition, information associated a weather condition, andinformation associated with a velocity of the vehicle.

In some embodiments, processor 118 may receive the input from adetermination performed by processor 118 itself. In such an example,processor 118 may determine the current driving environment based oninformation from one or more previous (and/or the current) scans of thefield of view. For example, the processor may determine that the currentdriving environment is urban based on the presence of numerous vehiclesand/or buildings in close proximity to the vehicle. By way of furtherexample, the processor may determine that the current drivingenvironment is rural based on the presence of numerous trees and/or openland. Processor 118 may alternatively or concurrently determine thecurrent driving environment based on a speed of the vehicle and/or basedon map information (which may be stored or received and may includeupdated traffic information). For example, processor 118 may determinethat the current driving environment is an interstate or highway basedon sustained, high speeds of the vehicle and/or based on a location ofthe vehicle aligning with a known interstate or highway. By way offurther example, processor 118 may determine that the current drivingenvironment is a traffic jam based on frequent stopping of the vehiclewith sustained, low speeds and/or based on known traffic information.

Alternatively or concurrently, processor 118 may receive the input froma host vehicle processing unit (e.g., ECU 2904). The central computermay determine the current driving environment using the techniquesdescribed above with respect to processor 118. Similarly, processor 118may additionally or alternatively receive the input from a remotesystem. For example, processor 118 may receive an indication of theweather from a weather server or other source of updated weatherinformation. Similarly, processor 118 may receive an indication of thetraffic from a traffic server or other source of updated trafficinformation.

In some embodiments, processor 118 may receive the input indicative ofthe current driving environment from at least one of a GPS, a vehiclenavigation system, a vehicle controller, a radar, a LIDAR, and a camera,as shown in FIG. 29. For example, as explained above, processor 118 mayuse the vehicle's location as determined by the GPS and/or the vehiclenavigation system in combination with maps and/or traffic information toderive the current driving environment. In such an example, processor118 may align the vehicle's GPS location with a map to determine thatthe vehicle is on an interstate or may align the vehicle's GPS locationwith traffic information to determine that the vehicle is in a trafficjam. Similarly, processor 118 may use the speed, heading, or the likefrom the vehicle controller to derive the current driving environment,as explained above. Additionally or alternatively, processor 118 may useinformation from radar, LIDAR, and/or a camera to derive the currentdriving environment. For example, processor 118 may identify one or moreobjects using radar, LIDAR, and/or a camera, such as fields, trees,buildings, medians, or the like, and use the identified objects toderive the current driving environment.

Once the optical or computational budget has been allocated and a planfor applying the apportioned budgets, processor 118 (or other processingdevices) may implement the plan. For example, processor 118 may outputsignals for controlling the at least one light source 112 and/or lightdeflector 114, or any other component affecting light flux (spatial ortemporal) to a LIDAR FOV, in a manner enabling light flux to vary overscanning of the LIDAR FOV in accordance with the dynamically apportionedoptical budget. In some cases, application of the apportioned opticalbudget may result in more light flux to certain portions (e.g., ROIs) ofone or more LIDAR FOVs, which, in turn, may require reduced light fluxto other areas (e.g., regions of lower interest or non-interest). Toexecute a plan for implementing an allocated optical budget, processor118 may be configured to control the at least one light deflector 114 inorder to scan the FOV, and during a scanning cycle the at least onelight deflector 114 may be located in a plurality of differentinstantaneous positions. Further, processor 118 may coordinate the atleast one light deflector 114 and the at least one light source 112(e.g., synchronize their operation) such that when the at least onelight deflector is located at a particular instantaneous position, aportion of a light beam is deflected by the at least one light deflectorfrom the at least one light source towards an object in the field ofview, and reflections of the portion of the light beam from the objectare deflected by the at least one light deflector toward at least onesensor 116. In some cases, LIDAR system 100 may include a plurality oflight sources aimed at the at least one light deflector 114, andprocessor 118 may be configured to control the at least one lightdeflector 114 such that when the at least one light deflector 114 islocated at a particular instantaneous position, light from the pluralityof light sources is projected towards a plurality of independent regionsof the LIDAR FOV. Generally, processor 118 may coordinate the at leastone light source 112 and the at least one light deflector 114 inaccordance with the dynamically apportioned optical budget. More lightper unit time may be applied to regions of higher interest, and lesslight per unit time may be applied to regions of lower interest throughapplication of the apportioned optical budget. Moreover, based ondetections of objects in one or more portions of a LIDAR FOV, processor118 may prevent an accumulated energy density of light projected to thea particular portion (e.g., whether a region of interest or a region ofless interest) to exceed a maximum permissible exposure.

FIG. 30A provides a flow chart providing an example of a method 3000 forcontrolling a LIDAR system based on apportioned budgets consistent withthe disclosed embodiments. For example, at step 3002, processor 118 (orother available processing devices) may receive information indicativeof one or more platform conditions of the LIDAR system (PCLS). Asdescribed above, these PCLSs may include any conditions associated withthe LIDAR system 100 or the platform host on which it is deployed forwhich a non-uniform light apportionment may be desired. At step 3004,processor 118 may determine system constraints that may in part aid indefining an optical or computational budget (e.g., light outputcapabilities of available light sources, processing capabilities ofavailable CPUs, etc.). Based on the information acquired at steps 3002and 3004, processor 118 may determine an apportioned optical budgetand/or an apportioned computational budget at step 3006. At step 3008,processor 118 may develop a scanning plan for application of theapportioned budgets to the operation of one or more LIDAR systems. Atstep 3010, processor 118 may control the per-beam-spot light projection(e.g., light projection from a particular instantaneous position ofdeflector 114) by, for example, controlling the operation of lightsource 112 and deflector 114 based on the apportioned budgets. Forexample, more light flux per unit time may be provided to regions ofinterest than is applied to regions of less interest. At step 3012,processor may detect and process reflected light based on an output ofdetector 116, for example. At step 3014, processor 118 may determinewhether a prescribed application of the apportioned optical budget for aparticular beam spot is complete. If so, the process may return to step3010 for continued control of light project at another beam spot. Ifnot, then at step 3016, processor 118 may determine whether another beamspot projection is permissible (e.g., whether another projection wouldcomply with eye safety regulations, whether a maximum permissible amountof light flux for a particular beam spot would be exceeded, etc.). Ifanother projection is not permitted, the process may return to step 3010for continued control of light project at another beam spot. If anotherprojection is permitted, then at step 3018, processor 118 may determinewhether another projection at the particular beam spot is needed (e.g.,whether sufficient data or detections have already been obtained basedon previous projections associated the particular beam spot orpreviously illuminated pixels). If an additional projection is notneeded, the process may return to step 3010 for continued control oflight project at another beam spot. Optionally, processor 118 may decideto redistribute the remaining unused power allocated to the present beamspot for at least one other beam-spot in the same scanning cycle. If anadditional projection is warranted, then at step 3020, processor 118 maycause an additional light projection at the particular beam spot, beforereturning to step 3012 for detection and processing of reflected light.

FIG. 30B provides a flow chart representation of an exemplary method3050 for controlling a LIDAR system according to the presently disclosedembodiments. Step 3062 may include accessing an optical budget stored inmemory, the optical budget being associated with at least one lightsource and defining an amount of light that is emittable in apredetermined time period by the at least one light source. Step 3064may include receiving information about a vehicle operational parameter,including at least one of: an environmental condition, a drivingdecision, and a power management mode. Based on the receivedinformation, step 3066 may include dynamically apportioning the opticalbudget to a field of view of the LIDAR system based on at least two of:scanning rates, scanning patterns, scanning angles, spatial lightdistribution, and temporal light distribution. Step 3068 may includeoutputting signals for controlling the at least one light source in amanner enabling light flux to vary over scanning of the field of view inaccordance with the dynamically apportioned optical budget.

In some embodiments, dynamically apportioning the optical budget basedon spatial light distribution may include projecting, during a singlescanning cycle, more light towards a first portion of the field of viewthan towards a second portion of the field of view. In a followingscanning cycle, dynamically apportioning the optical budget based onspatial light distribution may include projecting, during that followingscanning cycle, more light towards the second portion of the field ofview than towards the first portion of the field of view. The method mayfurther include obtaining an identification of the first portion as aregion of interest and an identification of the second portion as aregion of non-interest (or lower interest). The method may also includedetermining an existence of an object in the second portion andpreventing an accumulated energy density of the light in the secondportion from exceeding a maximum permissible exposure.

In another example for how an apportioned optical budget may be appliedduring operation of a LIDAR system, processor 118 may be configured toapportion more of an optical budget (e.g., more flux/FOV) to aparticular LIDAR system installed on a vehicle based a PCLS indicativeof a failure of another LIDAR system on the same vehicle. Suchapportionment may at least partly compensate for the failed LIDARsystem. For example, the apportionment to the working LIDAR system mayinclude emitting pulses to parts of that LIDAR's FOV where during normaloperation no pulses (or few pulses) are usually sent. Such apportionmentmay also include changing deflector parameters in order to scan a widerFOV, for example.

To further illustrate this example, FIG. 31 provides a diagrammaticillustration of a vehicle including seven installed LIDAR systemspositioned at different locations in the vehicle. Each individual LIDARdevice may exhibit different parameters in terms of field of view,range, resolution, accuracy, etc. The installed LIDAR systems may beconnected by a bus (e.g. CAN bus) that provides communication accessbetween the systems and potentially other components as shown in FIG.29. During operation, the various LIDAR devices may broadcast theiroperational parameters to one another as part of a capability exchangebooting phase or on-demand status request. This exchange of informationmay enable the processor of another LIDAR system, such as LIDAR system#7 to recognize that LIDAR system #2 has failed (e.g., based on receivederror messages, health status indicators, etc.). In some cases, a faultydevice on the bus may not be able to report (for example it lost itspower supply). In that case the non-reporting system is no longerconnected to the shared bus and is assumed to be failed.

One or more other LIDAR systems may take an action to at least partiallycompensate for the failed LIDAR device. For example, as shown in FIG.31, failure of LIDAR system #2 may result in a blind spot for thevehicle sensory system. A monitoring layer in HW or FW (main controlleror a designated master LiDAR device connected to the bus) would detectthat LiDAR #2 is non-functional and would designate another LiDAR in thesystem to compensate for loss of coverage. In this specific exampleLiDAR #7 was found to be the best choice for compensating the loss ofcoverage, given its extended capabilities. LiDAR #7 is designated tooperate in a backup mode and extend its field of view in order to coverup for LIDAR #2 field of view. Increasing the scanning range of LiDAR #7may occur at the expense of some of its capabilities, decreased totalrange, resolution or frame rate. The full system at the level of thevehicle main controller would be notified of the updated sensors statewith a reduced set of performance parameters and compensate for thevehicle behavior. Similar to a narrow spare tire that limits the vehicleto 80 Km/h, the vehicle might be limited at top speed. The compensationof faulty sensors is ultimately driven by the need of an autonomousvehicle to maintain a minimum autonomic level in order to be able tosafely reach a service location without human intervention.

It is noted that optionally, computational resources may be shared by aplurality of sensors of two or more types (e.g. LIDAR, camera,ultrasound sensor, radar) or allocated to the processing of detectioninformation arriving from sensors of different types. This may beimplemented, for example, by a host computer which integratesinformation from different sensors in a vehicle, such as an autonomouscar. The methods and processes disclosed above for apportionment ofcomputational budget (e.g. method 3000) may be extended may to apportioncomputational budget between processing information collected by sensorsof different types. Optionally, this may be further extended to allocatethe computational budget differently between FOV portion of each sensorout of a plurality of sensors of different types, while also shiftingcomputational resources between the different types of detection data,based on various parameters, such as platform condition of the vehicle,or any system installed in it. Such parameter may include, for example,any combination of one or more of the following: vehicle operationalparameter, an environmental condition, a driving decision, anavigational state of a vehicle, or a power management mode, systemparameter of one or more detection system (such as LIDAR, radar, etc.).It is that the apportionment of computational budget for processing of afirst sensor of a first type may be based on the processing of anothersensor of another type.

For example, if a camera detected a suspected object in one of its ROI,the apportioning processor may apportion more of the LIDAR computationalbudget for processing of detection information from that of the FOV, onthe expense of processing LIDAR detection information from other partsof the FOV. In another example, the apportioning processor may apportionthe computational budget based on detection results and/or platformparameters such that some parts of the FOV (which can of course bedefined in 3D, not just in 2D) would be primarily analyzed usingdetection information from a first type of sensors, while others partsof the FOV would primarily be analyzed using detection information froma second type of sensors. In yet more advanced allocation scheme, thehost (or another processor) may also shift power allocation betweensensors of different types, e.g., based on any one of the previouslydisclosed parameters, and according to any one of the aforementionedconsiderations, mutatis mutandis.

It is noted that many of the methods, processes and techniques for aLIDAR system which are discussed throughout the disclosure, when takenconsidered together with method 3000 (and with the entire discussion ofbudget apportionment), can be a part of a wider budget apportionmentscheme, which combines any two or more of the disclosed methods,processes and techniques. Such methods, processes and techniques may fitto different places in the disclosed budget allocation scheme. Forexample, some of these methods, processes and techniques may be used toas determining factors by which to allocate the budget to differentportions of the FOV; some of these methods, processes and techniques maybe used to as determining factors by which to restrict allocation of thebudget to different portions of the FOV; some of these methods,processes and techniques may be used for making use of the budgetallocated to different portions of the FOV, and so on.

According to some embodiments, a LIDAR system 100 may include:

-   -   a. A photonic emitter assembly (PTX) such as projection unit 102        (or a part thereof), to produce pulses of inspection photons        wherein the pulses are characterized by at least one pulse        parameter;    -   b. A photonic reception and detection assembly (PRX) to receive        reflected photons reflected back from an object, the PRX        including a detector (e.g. detector 116) to detect the reflected        photons and to produce a detected scene signal (e.g. by        processor 118). The photonic reception and detection assembly        may include sensing unit 106 (or a part thereof) and processing        unit 108 (or a part thereof);    -   c. A photonic steering assembly (PSY) such as scanning unit 104        (or a part thereof) functionally associated with both the PTX        and the PRX to direct the pulses of inspection photons in a        direction of an inspected scene segment and to steer the        reflection photons back to the PRX; and    -   d. a closed loop controller (herein below also “controller”)        which may be implemented by processing unit 108 (or a part        thereof, such as at least one processor 118), to: (a) control        the PTX, PRX and PSY, (b) receive the detected scene signal from        the detector and (c) update the at least one pulse parameter at        least partially based on the detected scene signal.

According to some embodiments, at least one pulse parameter may beselected from the following group: pulse power intensity, pulse width,pulse repetition rate pulse sequence, pulse duty cycle, wavelength,phase and/or polarization.

According to some embodiments, the controller may include a situationalassessment unit to receive the detected scene signal and produce ascanning/work plan. The work plan may include some or all of adetermined budget allocation, and may also include additionaloperational decisions (e.g., scanning pattern). The situationalassessment unit may receive a photonic steering assembly feedback fromthe photonic steering assembly. The situational assessment unit mayreceive information stored on a memory. Optionally, the information maybe selected from the following list: laser power budget (or any otherform of optical budget), electrical operational characteristics and/orcalibration data. The situational assessment unit may use the photonicsteering assembly feedback to produce the scanning/work plan. Theoptical budget (e.g. laser power budget) may be derived from constraintssuch as: eye safety limitations, thermal budget, laser aging over timeand more.

According to some embodiments, the work plan may be produced based on(a) real-time detected scene signal (b) intra-frame level scene signaland (c) interframe level scene signal accumulated and analyzed over twoor more frames.

According to some embodiments, the detector may be a dynamic detectorhaving one or more detector parameters and the closed loop controllermay update the detector parameters based on the work plan. The detectorparameters may be selected from the following group: scanning direction,frame rate, sampling rate, ambient light effects, mechanical static anddynamic impairments, dynamic gating for reducing parasitic light,dynamic sensitivity, dynamic bias, and/or thermal effects. The PSY mayhave one or more steering parameters and the closed loop controller mayupdate the steering based on the work plan. The steering parameters maybe selected from the following group: scanning method, power modulation,single or multiple axis methods, synchronization components. Optionally,the situational assessment unit may receive a host-feedback from a hostdevice and use the host feedback to produce or contribute to the workplan.

According to some embodiments, processor 118 may include situationalassessment logic or circuitry such as situational assessment logic(SAL). The SAL may receive detected scene signals from detector 116 aswell as information from additional blocks/elements either internal orexternal to scanning unit 104.

According to some embodiments, the scene signal may be assessed andcalculated with or without additional feedback signals such as aphotonic steering assembly feedback PTX feedback, PRX feedback and hostfeedback and information stored in memory 2902 in a weighted means oflocal and global cost functions that determine a scanning/work plan suchas a work plan signal for scanning unit 104 (such as: which pixels inthe FOV are scanned, at which laser parameters budget, at which detectorparameters budget). Accordingly, processor 118 may be a closed loopdynamic controller that receives system feedback and updates thesystem's operation based on that feedback. The scanning work plan, forexample, may be developed for implementing an apportioned optical orcomputational budget.

According to some embodiments, there may be provided a scanning unit 104for scanning one or more segments of a scene, also referred to as scenesegments. The device may include one or more photonic emitter assemblies(PTX), one or more photonic reception and detection assemblies (PRX), aphotonic steering assembly (PSY) and a situationally aware processoradapted to synchronize operation of the PTX, PRX and PSY, such that thedevice may dynamically perform active scanning of one or more scenesegments, or regions, of a scene during a scanning frame. Activescanning, may include transmission of one or more photonic inspectionpulses towards and across a scene segment, and when a scene elementpresent within the scene segment is hit by an inspection pulse,measuring a roundtrip time-of-flight for the pulse to hit the elementand its reflections to return, in order to estimate a distance and a(relative) three dimensional coordinate of point hit by the inspectionpulse on the scene element. By collecting coordinates for a set ofpoints on an element, using a set of inspection pulses, a threedimensional point cloud may be generated and used to detect, registerand possibly identify the scene element.

Processor 118 may be a situationally aware controller and maydynamically adjust the operational mode and operational parameters ofthe PTX, PRX and/or PSY based on one or more detected and/or otherwiseknown scene related situational parameters. According to someembodiments, processor 118 may generate and/or adjust a work plan suchas a scanning plan for scanning portions of a scene to implement anapportioned optical or computational budget, as part of a scanning frameintended to scan/cover one or more segments of the scene, based on anunderstanding of situational parameters such as scene elements presentwithin the one or more scene segment. Other situational parameters whichmay be factored in generating the scanning plan may include a locationand/or a trajectory of a host platform carrying a device according toembodiments. Yet further situational parameters which may be factored ingenerating the scanning plan may include a topography, include roadslope, pitch and curvature, surrounding a host platform carrying adevice according to embodiments.

The scanning plan may include: (a) a designation of scene segmentswithin the scene to be actively scanned as part of a scanning frame, (b)an inspection pulse set scheme (PSS) which may define a pulsedistribution pattern and/or individual pulse characteristics of a set ofinspection pulses used to scan at least one of the scene segments, (c) adetection scheme which may define a detector sensitivity or responsivitypattern, (d) a steering scheme which may define a steering direction,frequency, designate idle elements within a steering array and more. Inother words, the scanning plan may at least partially affect/determine aPTX control signal, steering parameters control, PRX control, and/ordetector control parameters so that a scanning frame is actively scannedbased on scene analysis and the apportioned optical and/or computationalbudgets.

The discussion below provides additional examples of controlling one ormore scans of a LIDAR FOV based on determined optical and/orcomputational budgets. For example, based on a current detected orinferred driving environment, processor 118 may coordinate the controlof the at least one light source with the control of the at least onelight deflector to dynamically adjust an instantaneous detectiondistance by varying an amount of an optical budget spatially appliedacross a scan of the field of view. For example, processor 118 mayincrease the amount of light projected and/or decrease the spatialdistribution of light to increase the instantaneous detection distancein certain regions of the FOV (regions of interest). By way of furtherexample, processor 118 may decrease the amount of light projected and/orincrease the spatial distribution of light to decrease the instantaneousdetection distance in other regions of the FOV (regions of lowerinterest).

Deflector Feedback Control in Lidar

In some embodiments, as noted previously, LIDAR system 100 may beincorporated onto a vehicle. Due to engine operation and motion overroads and other surfaces, a certain amount of vibration may result andthis vibration may interfere with operation of LIDAR system 100. Forexample, vibrations may be transferred to any of the components of LIDARsystem 100 and may affect their performance and/or the overallperformance of the system. In some cases, vibration of the light sourceand/or the light deflector may result in variations in a direction oflight emitted towards the LIDAR field of view (“FOV”), reducedcollection of light from objects in the FOV, uncertainties in deflectorposition and/or instantaneous FOV position, and/or inefficienciesintroduced into the deflector/sensor coupling. As a result, regions ofthe LIDAR FOV may not be illuminated as intended (e.g., as exemplifiedby the differences between intended FOV 3220 versus actual FOV 3222 inFIG. 32A), objects in the LIDAR FOV may go undetected, object may bedetected in erroneous directions, and/or object detections may result inless than desirable resolution levels.

To counter such effects, in some embodiments, LIDAR system 100 mayincorporate a vibration suppression system 3200 (e.g., FIG. 32A-B). Insome cases, LIDAR system 100 may determine the presence of vibration andmay take one or more actions to reduce or eliminate the effects of suchvibration. LIDAR system 100 may determine the presence of vibrationthrough any suitable technique. For example, in some cases, vibrationmay be detected using one or more sensors associated with the vehicle orwith LIDAR system 100 itself. Such sensors may include one or moreaccelerometers, strain gauges, or any other suitable type of sensor. Insome cases, vibration may be detected based on feedback received fromdeflector 114. That is, in some cases, the vibration suppression systemof LIDAR system 100 may respond to vibrational feedback determined basedon mirror position data associated with deflector 114 (e.g., usingmirror position feedback sensors illustrated in FIG. 32C to detectmovements of deflector 114 resulting from vibration, as well as, FIGS.62, 65, 67, 76, 77, and 84). Variations in mirror position as a resultof vibration may result from any source of vibration coupled directly orindirectly to LIDAR system 100. For example, such sources of vibrationmay result from engine operation, wheels rolling over a road surface,mechanical movements of vehicle components (including movements ofcomponents of LIDAR system 100), etc.

In addition to—or as an alternative to—being capable of countering someor all of the effects of vibration on the LIDAR system 100, vibrationsuppression system 3200 of LIDAR system 100 may also be capable ofcountering effects caused by uncertainties in positioning of themirrors. For example, when using a piezo-electrically actuated MEMSmirror, the piezo-electric actuation may include a certain amount ofhysteresis, which means that a certain control voltage may notnecessarily result in desired positioning of the mirror due to ambiguityin mirror position compared to controlling voltage. Therefore, aposition feedback mechanism, such as position feedback mechanism 3256 ofFIG. 32C (e.g., FIGS. 62, 65, 67, 76, 77, and 84), may be useful tocounter such effects, which may be present on any type of installment ofLIDAR system 100 (e.g., installations on moving platforms, such asvehicles, or on stationary objects, such as buildings, infrastructure,etc.). It is further noted that sensors 3228 (e.g. FIG. 32B) may be usedto obtain data indicative of position, orientation, velocity oracceleration of the at least one light deflector. These determinedinformation regarding the state of the light deflector may be determinedregardless of the reasons for diversions (e.g., vibrations, hysteresis,temperature effects), and may be used in the feedback control of thelight deflector to improve detection accuracy and operability of LIDARsystem 100 (e.g., in the examples provided below), mutatis mutandis.

In a LIDAR system configured to suppress the effects of vibration oruncertainties in light-deflector position, the system 3200 may includeat least one processor configured to control at least one light sourcein a manner enabling light flux of light from the at least one lightsource to vary over scans of a field of view; control positioning of atleast one light deflector to deflect light from the at least one lightsource in order to scan the field of view; and obtain data indicative ofvibrations of a vehicle on which the LIDAR system is deployed. Based onthe obtained data indicative of sensed vibration, the at least oneprocessor may determine adjustments to the positioning of the at leastone light deflector in order to compensate for the vibrations of thevehicle. The at least one processor may also implement the determinedadjustments to the positioning of the at least one light deflector tosuppress on the at least one light deflector, at least part of aninfluence of the vibrations of the vehicle on the scanning of the fieldof view.

FIG. 32A illustrates an exemplary vibration suppression system 3200 andvehicle 3210 on a bumpy road surface. Vehicle 3210 may be equipped withvarious types of sensors for detecting the presence of vibrations and/orcharacteristics associated with sensed vibrations. For example, in someembodiments, vehicle 3210 may include sensor units and/or vibrationsensors deployed at various locations on the vehicle. Such sensors maysense vibrations associated with the wheels, engine, body, etc. of thevehicle resulting from movement of the vehicle over a road or othersurface, operation of an engine of the vehicle, operation of one or moreother components of the vehicle, or any other potential source ofvibration imparted to vehicle 3210. For example sensor unit 3206,including sensor 3216 may be positioned in an area near an engine of thevehicle and may monitor vibrations associate with the engine.Additionally, one or more sensor units 3208, including sensors 3218, maybe positioned in an area near or on wheels associated with the vehiclein order to monitor vibrations associated with the wheels of thevehicle. The vehicle may also be equipped with one or more vibrationsensors 3219 positioned near to, on, or in LIDAR system 100 fordetecting vibration at a location near to or in LIDAR system 100.

Sensor 3216, 3218, and/or 3219 may include any type of sensor capable ofmeasuring at least one characteristic of vibration or an effect ofvibration, including, for example, force, acceleration, torque, strain,stress, voltage, optical deflections, etc. Such sensor 3216, 3218,and/or 3219 may be connected to one or more processors associated withLIDAR system 100, either directly or indirectly, via wired or wirelessconnections and may communicate to the one or more processors of theLIDAR system information indicative of the sensed vibration.

In addition to sensors 3216, 3218, and/or 3219, LIDAR system 100 may beequipped with one or more sensors or may be configured with sensingcapability to detect the presence of vibration and/or one or morecharacteristics of sensed vibration (e.g. sensor 3228 of FIG. 32B). Asdiscussed in more detail below, one or more processors associated withLIDAR system 100 may include programming enabling detection of vibrationpresent on deflector 114, for example. Such vibration may be detected,e.g., by monitoring movements of deflector 114, including movements notintentionally imparted to deflector 114 as part of a LIDAR FOV scan. Forinstance, FIG. 32B illustrates vehicle vibration compensation system3200 with LIDAR system 100 components, as well as, sensor 3228 incontact with scanning unit 104 and deflector 114. Sensor 3228 may beused to obtain data indicative of position, orientation, velocity oracceleration of the at least one light deflector 114. Also, intended FOVscan 3220 incorporates the instantaneous FOV 3224 and the actualinstantaneous FOV 3226 as scanned by deflector 114. Vibrations presentin the scanning unit 104 cause discrepancies between the intended andactual instantaneous field of views (3224 and 3226 respectively). Sensor3228 may detect the vibrations affecting deflector 114. It should befurther noted that FIG. 32B illustrates a bi-static embodiment, butalternative cases may incorporate a monostatic design.

Turning back to FIG. 32A, the presence of vibrations on vehicle 3210 mayinterfere with the operation of LIDAR system 100. For example, asvehicle 3210 progresses along a road towards object 3202. LIDAR system100 may direct a certain amount of light flux toward object 3202 duringa scan of the LIDAR FOV. As previously described, this light fluxdirected to a particular sub-region of the LIDAR FOV (e.g., where object3202 resides) may be accomplished by causing light projecting unit 102to provide light to light deflector 114 located in an instantaneousposition such that light is projected toward the FOV sub-regioncontaining object 3202. In the presence of vibration, however, deflector114 may experience movements that cause light, which was intended to bedirected to the sub-region in which object 3202 resides, to be directedat least partially to regions of the LIDAR FOV not intended to receivethe light. As a result, the ability of LIDAR system 100 to detect object3202 and provide information sufficient for generating suitable depthmaps including details of object 3202 and its position may be degraded.To combat this effect of vibration, processing unit 108 of LIDAR system100 may detect the vibrations, including one or more characteristics ofthose vibrations, based on outputs received from sensing unit 106,sensor 116, and/or deflector-position monitoring units. Processing unit108 may cause deflector 114 to move in such a way that counteracts atleast a portion of the movement imparted to deflector 114, lightprojecting unit 102, sensing unit 106, or any other component of LIDARsystem 100 affecting light projection, collection, or detection. Forexample, in some embodiments, processing unit 108 including one or moreprocessors 118, may monitor the position or orientation of deflector114, compare the monitored position with an intended instantaneousposition/orientation, and if a difference is determined, processor 118may cause deflector 114 to move toward the intended instantaneousposition/orientation. Using such a feedback approach, processor 118 maycounteract effects of vibrations that tend to displace deflector 114from its intended position or orientation. In some embodiments,processor 118 may be configured to cause vibration-reducing orcancelling movements to any movable component of LIDAR system 100 inorder to mitigate the effects of sensed vibrations.

The sections below further elaborate on the vibration-detection andvibration suppression capabilities of system 3200.

The presently disclosed embodiments may include a processor 118 (i.e.CPU 3234) configured to determine an instantaneous angular position(e.g. using θ, φ coordinates) of the at least one light deflector 114(i.e. mirror 3236). The term “instantaneous angular position” refers toan instantaneous position of the at least one deflector which causeslight to be deflected towards (and/or from) a given angular direction(e.g. indicated by θ, φ). Such a determination may be based on at leastone of optical measurements, capacitance measurements, piezo resistancemeasurements, dielectric constant measurement, and piezo polarizationmeasurements from one or more of the vibration sensors associated withvehicle 3210 or LIDAR system 100 (e.g., sensors associated with lightdeflector 114).

As discussed above, vibrations may be detected using one or more sensors3216, 3218, and/or 3219. Such sensors may include one or moreaccelerometers, strain gauges, or any other type of sensor suitable forsensing vibration or at least one characteristic of vibration.Additionally, as noted, LIDAR system 100 may be equipped with dedicatedvibration sensors (i.e. sensor 3228) or may detect vibration using oneor more components of systems used for scanning the LIDAR FOV. Forexample, in some embodiments, vibrations may be detected using deflector114 and position feedback sensors 3256 shown in FIG. 32C.

Shown in FIG. 32C is an exemplary pivotable mirror configurationincluding mirror 3306 which can be moved in two or more axes (e.g., θ,φ). As indicated in FIGS. 32C-G, mirror 3236 may be included indifferent configurations, including, for example, rectangular, square,circular, or rounded mirror shapes. Processor 118 may be configured tocontrol at least one deflector 114, including, for example, a positionof mirror 3236, during scans of the LIDAR FOV. Processor 118 may alsocontrol movement of mirror 3236 in order to provide a desired scanningrate, scanning pattern, spatial light distribution, temporal lightdistribution, etc.

For instantaneous directional control, steering unit 3232 (i.e. scanningunit 104) including mirror 3236 may also include an electricallycontrollable electromechanical driver, such as actuation driver 3238.Actuation driver 3238 may cause movement or power to be relayed to anactuator/cantilever/bender such as actuator 3240. Actuator 3240 may bepart of a support frame such as frame 3241 or they may be indirectlyconnected. Additional actuators such as actuators 3242, 3244 and 3246may each be controlled/driven by additional actuation drivers as shown,and may each have a support frame consistent of multiple layers 3243,3245 and 3247 (appropriately). It is understood that frames 3241, 3243,3245 and/or 3247 may comprise a single frame supporting all of theactuators or may be a plurality of interconnected frames. Furthermorethe frames may be electrically separated by isolation (Isn) elements orsections (as shown). Optionally, a flexible interconnect element orconnector, such as spring 3248, may be utilized to adjoin actuator 3240to mirror 3236, to relay power or movement from actuation driver 3238 tomirror 3236. Actuator 3240 may include two or more electrical contactssuch as contacts 3240A, 3240B, 3240C and 3240D. Optionally, one or morecontacts 3240A, 3240B, 3240C and/or 3240D may be situated on frame 3241or actuator 3240 provided that frame 3241 and actuator 3240 areelectronically connected. According to some embodiments, actuator 3240may be a semiconductor which may be doped so that actuator 3240 isgenerally conductive between contacts 3240A-3240D and isolative inisolation 3250 and 3252 to electronically isolate actuator 3240 fromactuators 3242 and 3246 (respectively). Optionally, instead of dopingthe actuator, actuator 3240 may include a conductive element which maybe adhered or otherwise mechanically or chemically connected to actuator3240, in which case isolation elements may be inherent in the areas ofactuator 3240 that do not have a conductive element adhered to them.Actuator 3240 may include a piezo electric layer so that current flowingthrough actuator 3240 may cause a reaction in the piezo electric sectionwhich may cause actuator 3240 to controllably bend.

CPU 3234, which may be incorporated, for example, into processing unit108, may output/relay to mirror driver 3254 a desired angular positionfor mirror 3236 described by θ, φ parameters. Mirror driver 3254 may beconfigured to control movement of mirror 3236 and may cause actuationdriver 3238 to push a certain voltage to contacts 3240C and 3240D inorder to attempt to achieve specific requested values for θ, φdeflection values of mirror 3236 based on bending of actuators 3240,3242, 3244 and 3246. According to some embodiments, position feedbackcontrol circuitry may be configured to supply an electrical source (suchas voltage or current) to a contact such as contact 3240A (or 3240B) andthe other contact such as 3240B (or 3240A, appropriately) may beconnected to a sensor within position feedback 3256, which may beutilized to measure one or more electrical parameters of actuator 3240to determine a bending of actuator 3240 and appropriately an actualdeflection of mirror 3236. It is further understood that by determiningthe bend of actuator 3240 and appropriately deflection mirror 3236, theCPU 3234 in turn determine real-time position of the light deflector.

Additional positional feedback similar to position feedback 3256 and anadditional actuation driver similar to actuation driver 3238 may bereplicated for each of actuators 3242-3246 and mirror driver 3254 andCPU 3234 may control those elements as well so that a mirror deflectionis controlled for all directions. The actuation drivers includingactuation driver 3238 may push forward a signal that causes anelectro-mechanical reaction in actuators 3240-3246 which each, in turnis sampled for feedback. The feedback on the actuators' (3240-3246)positions serves as a signal to mirror driver 3254 enabling it toconverge efficiently towards the desired position θ, φ set by the CPU3234, correcting a requested value based on a detected actualdeflection.

In addition to the described operation of positioning mirror 3236 andobtaining feedback. e.g., via 3242 A/B, 3244 A/B, or 3246 A/B and theposition feedback sensor, such elements among others may be used fordetecting vibration. For example, processor 118 may monitor feedbackfrom the position feedback sensor in order to determine data indicativeof vehicle vibrations (or LIDAR system vibrations). As discussed above,the vehicle vibration compensation system may utilize measured reflectedoptics data acquired from deflector. Scanning unit 104, like shown inFIGS. 3A-3C, or LIDAR system 100 may utilize piezoelectric actuatormicro electro mechanical (MEMS) mirror devices for deflecting a laserbeam scanning a field of view (FOV). Mirror 3236 deflection is a resultof voltage potential/current applied to the piezoelectric element thatis built up on actuator 3240. Mirror 3236 deflection is translated intoan angular scanning pattern that may not behave in a linear fashion, fora certain voltage level actuator 3240 does not translate to a constantdisplacement value. A scanning LIDAR system where the FOV dimensions aredeterministic and repeatable across different devices is optimallyrealized using a closed loop method that provides an angular deflectionfeedback from position feedback and sensor 3256 to mirror driver 3254and/or CPU 3234. Reflected optics not only can provide relevant data forthe LIDAR system (e.g., reflected light from a particular sub-region ofthe LIDAR FOV used to create depth maps), but CPU 3234 can also usemeasured optic data as a basis detecting vibrations. For example, if aspot of light reflected by mirror 3236 onto sensor 116, for example, isdetermined to move relative to the sensor, especially if the movement isconsistent with frequencies, amplitudes, etc. associated with vibration,then the direction and degree of movement of the collected light beammay enable processor 118 to detect the presence of vibration and alsoone or more characteristics of the vibration.

Other techniques can also be used by processor 118 to detect thepresence of vibration. Returning to FIG. 32C and as discussed above, theposition feedback sensor may also be used to measure vibrations. Forexample, the position feedback sensor may sense signals at actuator3242, 3244 and/or 3246 via contacts 3242A or 3242B, 3244A or 3244Band/or 3246A or 3246B. The sensed signals may be used to determineactuator movement, which in turn, may be indicative of vibrations. Inone example for detecting the effects of vibration by monitoring theactuators and/or output of the position feedback sensor, processor 118may have caused mirror 3236 to move to a particular instantaneouslocation as part of a scan of the LIDAR FOV. Once mirror 3236 has beenmoved to its designated instantaneous position (e.g., in order to directlight to a particular sub-region of the LIDAR FOV), processor 118 mayexpect the mirror to remain in that position for a certain dwell timebefore the mirror is moved to its next instantaneous position. Duringthe dwell time, mirror 3236 may be expected to remain fixed in thedesignated instantaneous position, or to move in a pace which allowscontinuous steering of light to a specific instantaneous FOV, asdiscussed above in greater detail. Thus, during the dwell time, ifsignals are received at processor 118 indicating that mirror 3236deviates from its expected orientation, especially if that deviation isoscillatory, sporadic, random, above a certain frequency, above acertain threshold, etc., then processor 118 may determine that thesignals indicative of movement/deviation during the dwell time may beindicative of vibration. Likewise, processor 118 may also determine thatthe signals indicative of movement/deviation during the instantaneousposition scanning time are indicative of an external force applied tothe mirror. Optionally, processor 118 may use the signals indicative ofmovement/deviation during the instantaneous position scanning time assuch, without determining their cause. When processor 118 causes mirror3236 to be moved (e.g., between dwell times at different instantaneouslocations), if processor 118 observes signals from the position feedbacksensor that are not consistent with signals expected for the proscribedmovement, then processor 118 may determine that the inconsistent signalsmay be associated with vibrational effects. When processor 118 causesmirror 3236 to be moved (e.g., between dwell times at differentinstantaneous locations), if processor 118 observes signals from theposition feedback sensor that are not consistent with signals expectedfor the proscribed movement, then processor 118 may issue positioncontrol signals to at least one actuator of mirror 3236, in response tothe signals of the position feedback sensor. It will be clear to aperson of skill in the art that such position control signals may alsobe issued by processor 118 to any other type of light deflector 114,mutatis mutandis.

Determining and/or monitoring the position of mirror 3236 may be usefulnot only to detect vibrations, but may also be useful for counteringother causes of unintended mirror movement. For instance, FIG. 32D showsan example actuator-mirror coupling in accordance with certain disclosedembodiments. Actuator 3240 may be made of several layers and may includea piezoelectric layer 3241, a semi conductive layer 3243, and a baselayer 3245. The resistivity of the semiconductor layer 3243 may bemeasured in an active stage (denoted “Ractive” in the diagram) when themirror is deflected at a certain angular position and compared to theresistivity at a resting state (Rrest). A feedback including Ractive mayprovide information to measure/determine the actual mirror deflectionangle compared to an expected angle. Based on this information, if thereis a difference between the expected angle/orientation/position ofmirror 3236, then actuator 3240 may be controlled in order to alter theangle/orientation/position of mirror 3236 in conformance with what isexpected. The electrical conductivity of the silicon (or othersemiconductor) based actuator 3240 may vary in response to mechanicalstresses that actuator 3240 experiences. When actuator 3240 is at restthe electrical conductivity exhibited at the two contacts 3240A and3240B would be Rrest. The piezoelectric material of layer 3241, ifactivated (e.g., by applying electrical voltage), would exert force onactuator 3240 and cause it to bend. Additionally, vibrations experiencedby LIDAR system 100 may result in unintended movement(s) of mirror 3236,which can also cause bending of actuator 3240. Bending of actuator 3240in response to a mechanical force (whether caused by electricalactivation of the piezoelectric layer or whether induced as a result ofvibration) may result in a change of the electrical conductivity Ractiveexhibited at the two contacts 3240A and 3240B. The difference betweenRrest and Ractive may be correlated by a mirror drive (such as mirrordriver 3254 of FIG. 32C) into an angular deflection value that serves toclose the loop. This method may be used for dynamic tracking of theactual mirror position. And using this information in a feedback loop,processor 118 may cause application of electrical signals (e.g., supplycurrent/voltage) to actuator 3240 to oppose motion caused by vibration.

Each of FIG. 32E, which provides a diagrammatic representation of a dualaxis mems mirror (3270), FIG. 32F, which provides a diagrammaticrepresentation of a single axis mems mirror (3280), and FIG. 32G, whichdepicts a round mems mirror (3290), provides an example of a mirror andactuator assembly that may be used to detect movements of the mirrorcaused by vibration and to counter those movements through an activefeedback loop. The mirror and actuator coupling may be configured withvarious characteristics according to the requirements of a particularapplication. For example, in some embodiments, the light deflector(e.g., mirror 3236 suspended within an actuator frame) may have aresonance frequency below 1000 Hz. Further, the deflector may include aMEMS mirror array, each of the separate mirrors constituting a lightdeflector element. In some embodiments, each light deflector may includea single MEMS mirror having a width of at least 4.5 mm. In otherembodiments, each light deflector may include a two dimensional array ofmirrors, each mirror having a width of at least 2 mm. As noted, upondetection of at least one movement (especially but not limited tomovement which is indicative of vibration)—e.g., by monitoring one ormore indicators of movement of mirror 3236—processor 118 may controlvarious actuators to counter the movements. Such control may beperformed as part of a feedback loop in which control may seek to reduceor eliminate differences between an intended/expected position ormovement of mirror 3236 and an observedposition/motion/velocity/acceleration of mirror 3236. Reduction orelimination of differences between an intendedposition/orientation/velocity/acceleration of mirror 3236 and anobserved position/orientation/velocity/acceleration of mirror 3236 maybe accomplished by driving actuators (e.g., actuators 3240, 3242, 3244,and/or 3246) in a manner that causes mirror 3236 to move opposite tomotion imparted by vibration (or by any other force, as discussedabove), or to otherwise modify movement characteristics of mirror 3236.By continuously monitoring a position/orientation/velocity/accelerationof mirror 3236 and by driving mirror 3236 toward an intendedposition/orientation associated with an intended instantaneous positionof mirror 3236 (during a scan of the LIDAR FOV) as part of a feedbackloop, mirror 3236 may be guided to substantially the intendedposition/orientation despite the forces applied on the mirror 3236 (e.g.forces caused by vibration).

Alternatively or additionally, processor 118 may control a position ofmirror 3236 based on received outputs of one or more sensors, such assensors 3216, 3218, and/or 3219. In such embodiments, processor 118 maydetermine adjustments for countering observed vibrations, which mayinclude computing appropriate axis (θ, φ) parameter adjustments to movemirror 3236 to an intended instantaneous position. In some cases, theseadjustments may include moving deflector 114 with steering device 3232in order to compensate for computed acceleration, torque, strain, etc.determined based on outputs from sensors associated with the vehicleitself.

In addition to vibration suppression, LIDAR system 100 may also becapable of sensing and reacting to other movements that may beassociated with a platform (e.g., a vehicle) on which LIDAR system 100is mounted or otherwise associated. For instance, a processor (e.g.,processor 118, CPU 3234, etc.) may be further configured to collect dataindicative of an inclination of a vehicle (e.g., FIG. 33). Informationindicative of the inclination of the vehicle may be provide as an outputof one or more accelerometers, one or more three-dimensionalaccelerometers, an inertial measurement unit (IMU), etc. Based on thisinformation, adjustments may be made to one or more aspects of LIDARsystem 100. For example, in some embodiments, one or more mechanicalactuators may be activated in order to rotate LIDAR system 100 (or oneor more of its components, including deflector 114; a light projectorassembly including the light projector, one or more light deflectors,and light sensors; or any other components of LIDAR system 100 that atleast in part affect a location of the LIDAR FOV relative to aparticular scene) in a manner that counters changes in the vehicleinclination. Such countering of vehicle inclination may result in theLIDAR FOV, for example, remaining substantially fixed (at least for acertain period of time) relative to a scene despite changes in vehicleinclination. In other cases, the LIDAR FOV may vary relative to thescene, but by less than an amount normally associated with a particularchange in vehicle inclination. As an example, as the vehicle isapproaching the crest of a hill (e.g., a negative inflection), the LIDARsystem (or one or more of its components) may be moved such that theLIDAR FOV moves downward relative to the scene. Such a movement mayenable the LIDAR FOV to overlap with less sky and more road. Similarly,as the vehicle approaches an upward inflection (e.g., a positiveinflection) in a road, the LIDAR system (or one or more of itscomponents) may be moved such that the LIDAR FOV moves upward relativeto the scene. Such a movement may enable the LIDAR FOV to overlap with aregion of the scene including more distant portions of the road past theupward inflection.

As an illustrative example, FIG. 33 shows two similar scenes includingvehicle 110 with LIDAR system 100 traveling downhill in the direction ofa truck 3302. In scene A, LIDAR system 100 has a fixed field of view120A with minimal and maximal elevation points such that truck 3302 isnot detected. In this case, LIDAR system 100 would not detect truck 3302until a later time (e.g., when vehicle passes the positive inflectionpoint in the road causing the LIDAR FOV to move upward relative to thescene, thereby overlapping with a region including truck 3302). In sceneB, however, LIDAR system 100 has a dynamic field of view 120B which maybe positioned relative to the scene by adjusting an aiming direction ofLIDAR system 100 or one or more of its components, e.g., as discussedabove. In this example, the inclination of the vehicle as it drives downthe hill may be detected, and the dynamic FOV 120B may be adjusted suchthat it overlaps not with the bottom of the hill (as in scene A), butrather with a region farther along the road, where truck 3302 resides.As a result. LIDAR system 100 may detect truck 3302 earlier than itwould without dynamic FOV capabilities. Clearly, processor 118 may reactto various positions of vehicle 110, and driving downhill was providedas one example scenario only.

The processing unit 108 (including CPU 3234, for example) may accomplishsuch adjustments in a variety of ways. For instance, CPU 3234 mayimplement a constant feedback loop, from data collected by feedbackvarious sensors associated with the vehicle in order to cause changes ina position of LIDAR system 100. Alternatively or additionally, deflector114 (e.g., mirror 3236) may be steered in a manner that offsets changesin vehicle inclination.

A method for suppressing vibrations of a LIDAR system for use on avehicle may include controlling at least one light source in a mannerenabling light flux of light from the at least one light source to varyover scans of a field of view. The method further comprises controllingpositioning of at least one light deflector to deflect light from the atleast one light source in order to scan the field of view. The methodobtains data indicative of vibrations of the vehicle. Base on thatobtained data, the method adjusts the positioning of the at least onelight deflector for compensating for the vibrations of the vehicle. Andthe method further implements the determined adjustments to thepositioning of the at least one light deflector to thereby suppress onthe at least one light deflector, at least part of an influence of thevibrations of the vehicle on the scanning of the field of view.

Turning now to FIG. 34, it is further understood that a method forsuppressing vibrations of a LIDAR configured for use on a vehicle mayinclude controlling at least one light source in a manner enabling lightflux of light from the at least one light source to vary over scans of afield of view (step 3410). In addition, in some embodiments, the lightdeflector 114 has a resonance frequency below 1000 Hz. In step 3420, thefield of view may be scanned by controlling, or steering, the lightdeflector positioning to deflect light from the at least one lightsource. In step 3430, data indicative of vibrations of the vehicle,where several examples of collected data are explained above, may beobtained. Then, in step 3440, based on the obtained data, adjustmentsare determined for the positioning of the at least one light deflectorfor compensating for the vibrations of the vehicle. And step 3450indicates the method may implement the determined adjustments throughpositioning of the at least one light deflector in order to suppress oreliminate effects of vibrations on one or more scans of the LIDAR FOV.Additional embodiments may further comprise determining an instantaneousangular position of the light deflector, and altering the instantaneousangular position of the light deflector to compensate for a differencebetween the intended or required position and the instantaneous angularposition.

Steerable High Energy Beam

To aid in the adoption of LIDAR systems by the automotive industry,there may be an interest in LIDAR systems that exhibit capabilitiessimilar to certain aspects of human sight. For example, human sightprovides information (e.g., through the parallax offered by two eyesviewing a scene from slightly different positions) enabling anindividual to perceive a scene in three dimensions. In a road situation,such capability may enable a person to perceive an undulating road,uphill road segment, downhill road segment, pitching, yawing, speedbumpers, tight turns, berms, steep pathways (e.g., underground garage),etc., as depth in three dimensions. In addition, human sight may enablean individual to determine and/or predict which regions in a field ofview (or within a scene) may require more attention such that theindividual can focus on those areas. For example, when driving on astreet, regions where pedestrians and vehicles reside may require moreattention than the sky line, or regions of the individual's field ofview or regions in the scene that do not include objects that mayinteract with, e.g., the individual's own vehicle. Thus, in response todetermining the presence of such objects in a scene (or an environmentof the individual), the individual may direct more attention to theregions in which those object reside. It may be desirable to provideLIDAR systems with similar capabilities.

In a LIDAR system consistent with embodiments of the present disclosure,the system may generate a 3-D reconstruction of objects in theenvironment within the FOV of the LIDAR system. The disclosed LIDARsystems may include a “gazing” capability that mimics to some extenthuman's sight behavior where the active field of view is shifted towardsspecific surrounding regions according to environmental, road featuresas well as vehicle motion vectors in three degrees of freedom (3DOF) upto six degrees of freedom (6DOF). This capability may enable the LIDARsystem to provide increased sensing performance across a large field ofview by adaptively partitioning the FOV, for example, into segments thatare allocated with different levels of quality of service (QoS).

As noted above, LIDAR system 100 may include at least one processor 118,e.g., within a processing unit 108, that may control at least one lightsource 112 to cause the light source 112 to generate higher or lowerlight flux in certain regions of the FOV. For example, in response to alevel of interest associated with a particular region of the FOV, moreor less light may be provided to that particular region commensuratewith the level of interest. Portions of field of view 120 that havelower interest (e.g., such as regions away from the detected cars shownin FIG. 5B) may be allocated with lower levels of light flux or even nolight flux at all. In other areas of higher interest, however, (e.g.,such as regions in which objects are detected, like the regions wherecars are detected as shown in FIG. 5B) may be allocated with higherlight flux levels. Such allocations may avoid expenditure of lightenergy and detection resources in areas of lower interest, but mayenhance resolution and other performance characteristics in areas ofgreater interest. A higher or lower light flux may be generated byaltering a light source parameter (e.g., pulse timing, pulse length,pulse size, pulse amplitude, pulse frequency, and/or the like)associated with the first portion such that light flux directed to thefirst portion is greater than light flux directed to at least one otherportion of the field of view. Alternatively, processor 118 may alter alight source parameter associated with the first portion such that lightflux directed to the first portion is lesser than light flux directed toat least one other portion of the field of view. Flux differences mayalso be achieved by modifying deflector parameters (e.g., scanningpattern, steering rate), and by changing synchronization of light sourceand deflector.

Light allocation can also be based on a predetermined allocation patternacross the FOV. FIG. 35A illustrates an example of FOV over a planeperpendicular to a detection plane of the sensor, e.g. seen from a birdseye view for a horizontally pointing LIDAR system. In the example shownin FIG. 35A, the FOV is divided into three sectors, but more or fewersectors may be achieved. Each sector may have a certain light fluxdirected to it. As a result, each sector may exhibit a correspondingsignal to noise distinctiveness balance, and/or a correspondingdetection range associated with the amount of light provided to eachsector. Among the three sectors depicted in FIG. 35A, sector II has beenallocated with a greater light flux than either sector I or sector III.As a result, the LIDAR system may be capable of detecting similarobjects at a more distant range at sector II than at either sector I orsector III. Similarly, as shown, sector III has been allocated with morelight than sector I, but less light than sector II. As a result, sectorIII may enable detection of objects at a range greater than that ofsector I, but less than sector II. Of course, other light allocationpatterns may be possible. For example, in some embodiments, sector IImay be allocated with the greatest light flux, and sector I and sectorIII may each be allocated with substantially the same amount of lightflux. The greater level of light flux directed to the second sector mayat least partially compensate for laser signal loss over the distancebetween the light source and a target of interest. Moreover, the greaterlight flux directed to the second sector may also enhance the resolutionthat the system may be capable of providing in that sector and, in turn,may enhance the quality of service in that sector and for the LIDARsystem as a whole. The enhanced resolution may be enhanced temporalresolution, enhanced spatial resolution, or a combination of both.

Not only may different levels of light flux be allocated to thedifferent sectors of the FOV, but the shape and size of the sectors mayalso vary. For example, in some embodiments, sector II (e.g., the sectorof highest light allocation in the FIG. 35A embodiment) may occupy acentral region of the FOV, as shown in the illustrative example shown inFIG. 35A. In other words, as described above, the FOV may be dividedinto multiple sub-regions. Processor 118 may designate anyregion/sub-region in the FOV as sector II (or any other sector). Thus,light allocation caused by the processor 118 may include supplying acertain light flux level to one or more sub-regions included within aparticular sector. Furthermore, each sector/subsector contains at leastone pixel. Systems and methods of the present disclosure may collectdata on a pixel-by-pixel basis. To scan the FOV, processor 118 maycontrol at least one light deflector (e.g., light deflector 114 of FIG.1A, deflector 114A and/or deflector 114B of FIG. 2A, and/or one-waydeflector 214 of FIG. 2B) in order to scan the field of view. Forexample, processor 118 may cause mechanical movement of the at least onelight deflector to scan the field of view. Alternatively orconcurrently, processor 118 may induce a piezoelectric orthermoelectrical change in the at least one deflector to scan the fieldof view.

The sectors associated with the LIDAR system may include any suitablesize or any orientation or different solid angles. For example, in someembodiments, each sector may have a similar size (e.g., may occupy asimilar number of similarly sized FOV sub-regions, such as a similarnumber of “pixels”, a similar number of“beam spots”). In other cases,however, the sectors may have different sizes. For example, FIG. 35Cillustrates different sectors with different sizes and shapes.

The sectors may also be located within the LIDAR FOV with variousdifferent orientations. In the illustrative example shown in FIG. 35A,each sector occupies a full height of the LIDAR FOV, such that the LIDARFOV is divided vertically into three sectors (I, II, and III) eachoccupying the full height of the LIDAR FOV. This is not necessarily thecase in all embodiments, however. Rather, because processor 118 mayassign any FOV sub-region or group of sub-regions to a particularsector, such sectors may constitute vertical slices of the FOV (FIG.35A), horizontal slices of the FOV, or may take on various other shapesor patterns, as discussed in more detail below with respect to FIG. 36.Herein, for example, a sub-region may be an instantaneous FOV, which canbe moved within the FOV by altering the instantaneous position of atleast one deflector.

In addition, the size, shape, and/or range associated with each sectormay change in different scanning cycles. For example, after acquiring aframe over a scanning cycle of the FOV, light allocations to the varioussectors may be changed, the number of sectors may be changed, the sizeof the sectors may be changed, and/or the relative position of any ofthe sectors within the FOV may be changed. In an illustrative exampleshown in FIG. 35B, the light allocated to sector III in a later scan ofthe FOV has been changed relative to the amount of light allocated tosector III in an earlier scan of the FOV, as represented by FIG. 35A. Asa result, sector III in the FIG. 35B scan may be associated with lesslight flux and, therefore, a shorter detection range, lower signal tonoise ratio, etc. as compared to sector III in the FIG. 35A scan.Consequently, as illustrated in FIG. 35B, sector I and sector III mayhave a same detection range.

Furthermore, the position, size, shape, and/or light flux associatedwith different sectors may be varied over multiple scanning cyclesaccording to a predetermined pattern, based on detection feedback, basedon instructions or information provided by the host or another externalsystem, or based on any other suitable basis. In some embodiments, forexample, the relative position of a particular sector may be changedwithin the FOV across two or more scanning cycles of the FOV. As aresult, the particular sector, such as sector II, for example, may bemade to scan the FOV across multiple scans (for example, in a rasterpattern, in a sweeping motion, etc.). Additionally, an amount of lightflux provided to the available sectors may be varied from scan to scan.For example, compared to a scan associated FIG. 35A, the scanrepresented by FIG. 35B shows that the amount of light allocated tosector III has been reduced. As a result, a detection range of sectorIII may also be changed (e.g., reduced). Such changes in lightallocation may be made by processor 118 in response to a predeterminedsector scanning scheme, based on feedback (e.g., sensor output relatingto vehicle motion, LIDAR detections of one or more objects of interest,other sensors/detectors, etc.). Consequently, as illustrated in FIG.35B, processor 118 may determine a same detection range for twodifferent sectors in the FOV.

In one example, referring to FIG. 1A, the LIDAR system 100 may bedeployed on a vehicle 110, and the processing unit 108 may select apredefined scanning pattern for a particular sector (such as sector II)based on the driving mode of the vehicle. (e.g., pitching, yawing,rolling, stopping, etc.). As the vehicle moves, the processing unit 108may cause sector II to move from scan to scan in a sweeping motion. Suchchanges in position may enable the LIDAR system to effectively detecttarget objects (including those located at a range or ranges ofinterest). Additionally, the sweeping of a particular sector acrossmultiple scans of the LIDAR FOV may enable the system to track one ormore targets of interest across a plurality of scans. For example, iffrom scan to scan, the vehicle continues to move relative to a detectedobject, by moving the location of a detection sector relative to theFOV, (e.g., moving sector II in a sweeping motion across a plurality ofscans), the LIDAR system may keep track of one or more target objects asthe vehicle moves relative to those objects.

Another illustrative example may include situations in which the vehicle110 changes direction (e.g., making a left or right turns, making aU-turn, parking, etc.). In such cases, scanning of a particular sectoracross the FOV over a plurality of scan cycles may enable continuoustracking of a target object that would otherwise not be detected (orperhaps not be detected with a desired resolution) without scanning of aparticular sector across the FOV. While such scanning may occuraccording to a predetermined pattern (e.g., regular sweeping of therelative location in the FOV at a predetermined rate, location, etc.),the scanning of a particular sector may also be based on any othersuitable basis. For example, in one embodiment, the scanning may bebased on feedback associated with vehicle motion, as mentioned above. Asthe vehicle moves, sensors on the vehicle (e.g., speed sensors,accelerometers, etc.) may monitor the speed and orientation of thevehicle. In turn, the location of a particular sector in the FOV may bechanged from one scanning cycle to the next to at least partiallyaccount for the sensed motion of the vehicle. In one example, the sectorlocation may be changed such that a detected object (e.g., anothervehicle, a pedestrian, etc.) may be tracked at least partially within aparticular sector (e.g., sector II of FIG. 35A or 35B or sector IV ofFIG. 35C) over the course of a plurality of FOV scanning cycles.

Additionally, the relative movement of the sector within the FOV may bebased on other types of feedback. For example, if an object of interestdetected within a particular sector of the FOV (e.g., sector II), andthat object is determined to be moving relative to the LIDAR system, therelative motion of the object of interest may be taken into account whenassigning a subsequent location of a particular sector within the FOVduring one or more subsequent scans. For instance, as illustrated inFIG. 35C, if a target vehicle is crossing in front of the host vehicleincluding the LIDAR system and is crossing from right to left, therelative location of a particular sector (e.g., sector IV) may be sweptacross the FOV over multiple scans in order to track the motion of thetarget vehicle as it moves from right to left across the FOV. As aresult, the location of sector IV may also move right to left across theFOV over multiple scans of the FOV. The rate at which the sector ismoved to new locations in the FOV (e.g., the angular change of thesector location from scan to scan) may depend on the observed relativemovement characteristics of the target vehicle (e.g., its relativevelocity, acceleration, distance from the host vehicle, etc.).Correspondingly, FIG. 35D illustrates the FOV divided into sectorscorresponding to the sectors in FIG. 35C.

Alternatively and concurrently, the relative movement of the sectorwithin the FOV may be a sweeping pattern. Similar to the lightprojecting mode of a “lighthouse”, a particular sector can move acrossthe FOV or a portion of the FOV to detect any moving object and trackthem.

Alternatively and concurrently, processor 118 may cause the dimensionsof the center-of-frame a particular sector in a FOV (e.g. sector II) bereduced, based on the speed of the host vehicle, in order to increasedetection range ahead at the expense of wider scene understanding.

Sweeping a sector (or more than one sector) across the FOV from scan toscan may be done continuously (e.g., where the angular change of thesector is constant from scan to scan). Sweeping or one or more sectorsmay also be done in a non-continuous manner (e.g., the angular change ofthe sector from scan to scan is not constant).

One or more sectors of a FOV may also be designated by processor 118 toreceive little or no light flux. For example, if a dead zone is detected(e.g., one with few or no objects of interest) or a nearby object blocksa portion of FOV, there may be less need for additional information fromthat zone during one or more subsequent scans. As a result, a low lightflux sector or even a no light flux sector may be assigned to overlapwith the dead zone during one or more subsequent scans of the FOV. Inthat way, the energy usage/energy requirements of the LIDAR system maybe reduced. Additionally or alternatively, light energy that would havebeen available for allocation to the dead zone sector(s) may be freed upfor reallocation to one or more other sectors of higher interest.

As noted above, the FOV may be divided into one or more sectors, eachbeing made of any one or more sub-regions with the FOV. Such sectordivisions may include vertical sections of the FOV, horizontal sectionsof the FOV, or may include various other patterns. In one embodiment, asshown in FIG. 36, the FOV may be divided into three sectors (sector I,sector II, and sector III). Sectors I and III, in this embodiment,include vertical slices of the FOV. Sector II, however, is assigned tosub-regions of the FOV that are completely surrounded by the first andthird sectors. The location of sector II may be in a similar relativeposition within the FOV from scan to scan or may be moved. In someembodiments, sector II may be caused to sweep in multiple consecutivescanning cycles such that in each scanning cycle at least a part of thesecond sector is located below a horizon line or level. For example,when driving on an undulating road and an object of interest (e.g., apothole, another vehicle, a pedestrian, etc.) is detected on the road,it may be desirable to allocate more light flux toward the region of theobject of interest to increase the resolution in that area and toimprove capabilities in determining the characteristics of the object.Thus, in the manner described above, processor 118 may cause sector IIto track the object of interest from scan to scan based on sensedvehicle orientation, relative motion of the object of interest, or anyother criteria. Thus, as the vehicle on which the LIDAR system residesdrives down a hill, sector II may be caused to move upward from scan toscan to maintain overlap with the object of interest on the road ahead.Similarly, when the host vehicle drives up a hill, the location ofsector II in the FOV may be caused to move downward from scan to scan.As a result, despite the undulating road, the location of sector II(e.g., a high light flux allocation zone) within the FOV may move up anddown such that sector II overlaps with a region of the FOV substantiallybelow a horizon line.

FIG. 37 is a flowchart of example method 3700 for detecting objectsusing a LIDAR system. In step 3701, a processor (e.g., processor 118)controls at least one light source (e.g., light source 112) in a mannerenabling light flux of light from at least one light source to vary overa scanning cycle of a field of view (e.g., field of view 120), whereinthe light projected from the at least one light source is directed to atleast one deflector (e.g., light deflector 114) to scan the field ofview. In step 3702, a processor (e.g., processor 118) receives from atleast one sensor (e.g., sensor 116), reflections signals indicative oflight reflected from objects in the field of view (e.g., field of view120). In step 3703, a processor (e.g., processor 118) coordinates lightflux and scanning in a manner to cause at least three sectors to occurin a scanning cycle. Processor 118 may cause similar or different levelsof light flux to be supplied to each of the at least three sectors. Insome examples, the light flux supplied to the second sector may begreater than the light flux supplied to the first and third sectors.Processor 118 may also cause different point resolutions with respect toone or more of the available sectors. A “point resolution” may refer toa resolution of a point cloud map in which every point of one or morepoints of the point cloud map corresponds to a location in the object ora location on a face thereof. That is, if the average space between eachpoint is reduced and a number of points increase, the point resolutionmay be higher. And, the higher the point resolution becomes, the moreaccurate the information may be (e.g., spatial information, temporalinformation, etc.).

In step 3704, a processor (e.g., processor 118) may control the at leastone light source (e.g., light source 112) such that the light fluxsupplied to a first sector is substantially the same as the light fluxsupplied to a third sector, and a light flux level supplied to a secondsector is greater than the flux supplied to the first and third regions.As a result, a detection range associated with the second sector may beextended by at least 50% farther than a detection range associated withthe first sector or a detection range associate with the third sector.In step 3705, a processor (e.g., processor 118) may detect, based oninput from at least one sensor (e.g., sensor 116), an object in thesecond sector at a point resolution that is higher than a pointresolution provided by either the first sector or the third sector. Instep 3706, a processor (e.g., processor 118) may detect an object in thesecond sector using a second point resolution having an average spacebetween each point that is less than about 50% of an average spacebetween points in point resolutions associated with the first and thethird sectors. For example, when more accurate information in the secondsector is desired, the at least one processor may enhance the pointresolution by reducing the average space between each point in the pointresolution associated with the second sector. In step 3707, a processor(e.g., processor 118) may detect an object in the second sector, basedon input from the at least one sensor (e.g., sensor 116).

Parallel Capturing of Lidar Frames at Differing Rates

FIG. 38 is a diagram of illustrating a field of view 3802 of a LIDARsystem 3800. LIDAR system 3800 may operate as described above withreference to LIDAR system 100. In some embodiments the LIDAR system 3800includes one or more processors configured to control one or more lightsources in a manner enabling light flux to vary over a number of scansof a field of view 3802. Each scan of the field of view may result in acaptured frame. Each frame may include sensor output information foreach of the regions of the field of view to which light was directed andcollected during the scan. The field of view may include a near-fieldportion 3804 and a far-field portion 3806. In some cases, capturedframes may target detection of objects in the near-field portion. Inother cases, captured frames may target detection of objects in thefar-field portion. As discussed in more detail below, scans directed tothe near field (and the associated captured frames) may involve lowerlight flux and faster scan rates, as compared to scans directed to thefar-field portion of the FOV (and the associated captured frames).

As previously noted, the processor may control one or more lightdeflectors to deflect light from the light source to scan the field ofview 3802. For example, controller 118 may control the movement of theone or more deflectors to provide a desired scan rate. The processor mayimplement a near-field scanning rate for frames associated with scanningcycles that cover the near-field portion 3804 of the field of view.Processor 118 may implement a far-field scanning rate for framesassociated with scanning cycles that cover the far-field portion 3806 ofthe field of view.

During one or more scans for capturing one or more corresponding frames,processor 118 may control the light source in a manner enablingdetection of objects in the near-field portion 3804 of the field ofview. For example, processor 118 may cause the light source to emit acertain amount of light flux, emit light at a certain power level, etc.,appropriate for detection of objects in the near field (e.g., objectsless than 50 meters away, objects less than 100 meters away, etc.). Atother times, processor 118 may control the light source such that lightis emitted in a manner enabling detection of objects in the far-fieldportion 3806. For example, in capturing frames associated with detectionin the far-field, the light source may be caused to supply higheramounts of flux, light at a higher power level, etc. in order toincrease the LIDAR sensitivity to objects at a greater distance, toobjects having a lower reflectivity, etc. It should be noted that suchincreases in light flux may also enable detection of objects in the nearfield as well (including objects of lower reflectivity relative to otherobjects).

In some cases, such as when LIDAR system 3800 is associated with avehicle, when an object is nearer to the LIDAR system, there may be lesstime to react to a detected object than if the object is farther away.Therefore, in some embodiments, the near-field scanning rate may begreater than a scanning rate employed for acquiring frames thatconcentrate on the far-field, where reaction times may be longer. Insome embodiments the near-field scanning rate may at least five timesfaster than the far-field scanning rate. For example, in one exampleembodiment, the scanning rate for the near-field portion 3802 of thefield of view may be 25 frames per second, and the scanning rate for thefar-field portion 3804 of the field of view may be 5 frames per second.A faster scanning rate may provide increased feedback in a short timeperiod, and may allow the LIDAR system to detect near-field objects withenough time to react to the detected near-field objects (e.g., reactionsby an autonomous or semi-autonomous driving system; driver assistsystem; navigation system, etc.). Far-field detection may require alarger amount of light energy than near-field detection (e.g., as aresult of higher light flux levels, higher light source power levels,etc.). Adjusting the scanning rate of the far-field detection (e.g., bydecreasing the FOV scan rate relative to other scans that may focus onnear-field detections) may offer a benefit of reducing power consumptionof the LIDAR system, as compared to scans of the far-field region athigher scanning rates.

Objects in the near-field portion of the LIDAR field of view may includeobjects located relatively close to the LIDAR system. For example, insome embodiments, near-field objects may refer to objects located lessthan 50 meters from the LIDAR system. Similarly, far-field objects mayinclude objects located at a distance greater than near-field objects.For example, in some embodiments, far-field objects may include objectslocated more than 100 meters from the LIDAR system. In some embodiments,objects in the near-field portion of the field of view may be less than100 meters from the LIDAR system. In some embodiments objects in thefar-field portion of the field of view may be more than 50 meters fromthe LIDAR system. For example, in one illustrative embodiment, LIDARsystem 3800 may detect in a first frame a first car parked at a curb inthe near-field, e.g., 30 meters away. LIDAR system 3800 may also detectin a second frame the first car parked at a curb and a second car in thelane ahead in the far-field, e.g., 200 meters away. In other words, insome embodiments, the far-field frames may provide near-fieldinformation in addition to far-field information, such that the rate ofinformation received about the near-field may not be interrupted.

In some embodiments, the detection distance of the LIDAR systemassociated with the far-field frames may extend at least 50% fartherthan the detection distance associated with the near-field frames. Insome embodiments the detection distance associated with the near-fieldand far-field frames may be adjustable, for example, by adjusting lightflux/light energy levels. A far-field detection may require more power,as compared to near-field detection, as more light may be required togather object information from the far-field. As noted above, theincreased power consumption from far-field detection may be mitigated byreducing the frame scan rate for frame acquisitions associated withfar-field detection.

The processor may control one or more of the light deflectors to belocated in a number of different instantaneous positions during ascanning cycle. In some embodiments, at least one light deflector 114and at least one light source 112 may be coordinated such that the lightdeflector is in a position to deflect a portion of the light beamgenerated by the light source to an object in the field of view and todeflect the reflection from the object toward one or more sensors. Insome embodiments, one or more light sources may be aimed towards acommon area in the light deflector such that the processor may controlthe deflector to project the light from the light sources towards one ormore independent regions of the field of view.

In some embodiments, the processor may control the one or more lightsources to provide a particular spatial light distribution in a givenframe and different spatial light distribution in one or more subsequentframes. Additionally, the processor may control the light source to usea certain light-distribution scheme for the near-field frames and adifferent light-distribution scheme for the far-field frames. Forexample, as shown in FIG. 39, light may be emitted toward an area in thefar-field 3906 located near the horizon according to a far-fieldlight-distribution scheme. And less light may be emitted toward thehorizon in the near-field 3904 according to a near-fieldlight-distribution scheme. By focusing emitted light on the far-fieldhorizon, the LIDAR system may detect an object in the far-field, whilesaving resources to scan greater portions of the near-field for objects.Information on the nature, size, or other properties of an object in thefar-field may not need to be determined or detected until a detectedobjection is at a closer distance relative to the LIDAR system.

In some embodiments, the processor may receive information from one ormore sensors associated with a frame to detect object(s) located in thefar-field. In some embodiments, in a certain frame, the processor mayreceive information from a sensor indicating one or more objects arelocated in the far-field and/or one or more objects are located in thenear-field portion of the field of view.

In some embodiments, the resolution of acquired frames associated withthe far-field may be lower than a resolution of frames associated withthe near-field. While various expressions of such resolution may bepossible, in one example, the average spacing between points in thenear-field frames may be less than about 75% of the average spacingbetween points in the far-field frames. It is noted that a similardifferentiation scheme between frames may be used, mutatis mutandis,where high-resolution frames are acquired at a first frame rate, andlow-resolution frames are acquired at a second, higher, frame rate.

In some embodiments, the near-field scanning rate and/or far-fieldscanning rate may be implemented depending on the driving mode of avehicle containing the LIDAR system. For example, a vehicle driving in acity may benefit from an emphasis on near-field scanning as compared toa vehicle driving on a rural road. In other embodiments, the near-fieldscanning rate and/or far-field scanning rate may be implementeddepending on vehicle speed. For example, as vehicle speed slows, thescanning rates associated with either or both of the far-field and thenear-field may be reduced. Similarly, the scanning rates associated witheither or both of the far-field and the near-field may be increased asvehicle speed increases.

FIG. 40A is a flow chart of an exemplary process 4000 for emitting lightfrom a LIDAR system. In step 4010, a light source emits light to one ormore areas of the near-field portion of the field of view. If an objectexists in the near-field, light may be reflected off the object anddetected by one or more sensors of the LIDAR system in step 4020. Thecombination of steps 4010 and 4020 may form one scanning cycle. In someembodiments, the sequence of steps 4010 and 4020 may be repeated one ormore times as part of a single scanning cycle.

At the beginning of the next scanning cycle, at step 4030, light may beemitted from the light source at the far-field scanning rate. If anobject exists in the far-field, light may be reflected off the objectand detected by one or more sensors of the LIDAR system in step 4040.The combination of steps 4030 and 4040 may form another scanning cycle.In some embodiments, the sequence of steps 4030 and 4040 may be repeatedone or more times as part of a single scanning cycle. After Steps4010-4040 are completed, the sequence of scanning cycles may start overfrom step 4010.

FIG. 40B is a flow chart of another exemplary process for emitting lightfrom LIDAR system 100. At step 4502, processor 118 may determine whethera current FOV frame matches or is otherwise designated with a scan ratedesignated as a far-field scanning rate. If yes, then at step 4506,processor 118 may control light source 112 and deflector 114 accordingto a far-field illumination scheme. If no, then at step 4504, processor118 may control light source 112 and deflector 114 according to anear-field illumination scheme. At step 4508, reflected light may beacquired. At step 4510, the detected light may be analyzed, and at step4512, a 3-D depth map representation may be generated for the FOV basedon the detected light reflections.

Dynamic Mode of Operation Based on Driving Environment

In a vehicle having a LIDAR system consistent with embodiments of thepresent disclosure, driving environments may change throughout thecourse of a drive. For example, the vehicle may begin in an urban (orsuburban) environment and move to a rural environment during a trip.Other driving environments might include parking lots, traffic jams,tunnels, junctions, bridges, interstates or highways, and so on. Basedon various indicators of the environment (or based on direct input tothe system). LIDAR systems consistent with embodiments of the presentdisclosure may adjust one or more properties of a scan of a field ofview to account for the environment. For example, the LIDAR systems mayadjust an instantaneous detection distance, a spatial resolution, atemporal resolution, a signal-to-noise ratio, flux distribution acrossthe FOV, frame rate, a size of the field of view, aspect ratio of thefield of view, one or more pulse-transmission schemes, or the like.

Systems and methods of the present disclosure may thus allow foradjustment of one or more properties of a field-of-view scan, forexample, in response to a determined driving environment. FIG. 41Aillustrates an example method 4100 for altering detection distance in aLIDAR system. Although method 4100 of FIG. 41A adjusts detectiondistance, other properties, such as those discussed above, mayadditionally or alternatively be adjusted. Method 4100 may be performedby at least one processor (e.g., processor 118 of processing unit 108 ofLIDAR system 100 as depicted in FIG. 1A and/or two processors 118 ofprocessing unit 108 of the LIDAR system depicted in FIG. 2A).

At step 4101, processor 118 controls at least one light source (e.g.,light source 112 of FIG. 1A, laser diode 202 of light source 112 of FIG.2A, and/or plurality of light sources 102 of FIG. 2B) in a mannerenabling light flux of at least one light source to vary over scans of afield of view (e.g., field of view 120 of FIGS. 1A and 2A, field of view4203 of FIG. 42A, field of view 4207 of FIG. 42B, field of view 4211 ofFIG. 42C, field of view 4215 of FIG. 42D, field of view 4215′ of FIG.42E, field of view 4311 of FIG. 43). For example, processor 118 may varythe timing of pulses from the at least one light source. Alternativelyor concurrently, processor 118 may vary the length of pulses from the atleast one light source. By way of further example, processor 118 mayalternatively or concurrently vary a size (e.g., length or width orotherwise alter a cross-sectional area) of pulses from the at least onelight source. In a yet further example, processor 118 may alternativelyor concurrently vary the amplitude and/or frequency of pulses from theat least one light source.

At step 4103, processor 118 controls at least one light deflector (e.g.,light deflector 114 of FIG. 1A, deflector 114A and/or deflector 114B ofFIG. 2A, and/or one-way deflector 214 of FIG. 2B) to deflect light fromthe at least one light source in order to scan the field of view. Forexample, processor 118 may cause mechanical movement of the at least onelight deflector to scan the field of view. Alternatively orconcurrently, processor 118 may induce a piezoelectric orthermoelectrical change in the at least one deflector to scan the fieldof view. Alternatively or concurrently, processor 118 may inducesteering of an Optical Phased Array (OPA) light source, by modifyingrelative amplitude, phase or other signal characteristics of thedifferent emission sources of the OPA. Alternatively or concurrently,processor 118 may induce changing of active light emitters of avertical-cavity surface-emitting laser (VCSEL) array.

In some embodiments, the field of view (e.g., field of view 4215 of FIG.42D, field of view 4215′ of FIG. 42E, field of view 4311 of FIG. 43) mayinclude a plurality of portions (e.g., a first portion and a secondportion). For example, the portions may comprise halves, fourths, orother fractions of the area covered by the field of view. In otherexamples, the portions may comprise irregular, rather than symmetricand/or fractional, portions of the area covered by the field of view. Instill other examples, the portions may comprise discontinuous portionsof the area covered by the field of view.

In some embodiments, processor 118 may control the at least one lightdeflector such that, during a single scanning cycle, the at least onelight deflector is located in a plurality of different instantaneouspositions (e.g., the deflector is controlled such that the deflectormoves from or through one instantaneous position to another during thescan of the LIDAR FOV). For example, the at least one light deflectormay be moved continuously or non-continuously from one of the pluralityof positions to another (optionally with additional positions and/orrepetitions) during the scanning cycle.

In such embodiments, processor 118 may coordinate the at least one lightdeflector and the at least one light source such that, when the at leastone light deflector is located at a particular instantaneous position, aportion of a light beam is deflected by the at least one light deflectorfrom the at least one light source towards an object in the field ofview and reflections of the portion of the light beam are deflected fromthe object toward at least one sensor. Accordingly, the at least onelight deflector may direct a portion of the light beam toward the fieldof view and also receive a reflection from the field of view. Forexample, FIGS. 1A, 2B, and 2C depict examples in which a deflector bothdirects a portion of the light beam towards the field of view and alsoreceives a reflection from the field of view. In other embodiments, aportion of the light beam from the at least one light source may bedirected towards the field of view by at least one light deflectorseparate from at least one other light deflector that receives areflection from the field of view. For example, FIG. 2A depicts anexample in which one deflector directs a portion of the light beamtowards the field of view and a separate deflector receives a reflectionfrom the field of view. In some embodiments, the at least one deflectormay include a first group of one or more deflectors for (transmission)and a second group of one or more deflectors for (reception), which maybe different from each other.

In some embodiments, the at least one light source may comprise aplurality of light sources aimed at a common area of the at least onelight deflector. In such embodiments, processor 118 may control the atleast one light deflector such that, when the at least one lightdeflector is located at a particular instantaneous position, light fromthe plurality of light sources is projected towards a plurality ofindependent regions forming the field of view. An example of such anembodiment is depicted in FIG. 43, discussed below.

At step 4105, processor 118 receives input indicative of a currentdriving environment of the vehicle. For example, processor 118 mayreceive input that includes at least one of a rural-related indicationand an urban-related indication. By way of further example, processor118 may receive input that includes at least one rural-relatedindication, urban-related indication, information associated with alight condition, information associated a weather condition, andinformation associated with a velocity of the vehicle.

In some embodiments, processor 118 may receive the input from adetermination performed by processor 118 itself. In such an example,processor 118 may determine the current driving environment based oninformation from one or more previous (and/or the current) scans of thefield of view. For example, the processor may determine that the currentdriving environment is urban based on the presence of numerous vehiclesand/or buildings in close proximity to the vehicle. By way of furtherexample, the processor may determine that the current drivingenvironment is rural based on the presence of numerous trees and/or openland. Processor 118 may alternatively or concurrently determine thecurrent driving environment based on a speed of the vehicle and/or basedon map information (which may be stored or received and may includeupdated traffic information). For example, processor 118 may determinethat the current driving environment is an interstate or highway basedon sustained, high speeds of the vehicle and/or based on a location ofthe vehicle aligning with a known interstate or highway. By way offurther example, processor 118 may determine that the current drivingenvironment is a traffic jam based on frequent stopping of the vehiclewith sustained, low speeds and/or based on known traffic information.

Alternatively or concurrently, processor 118 may receive the input froma host processing unit, for example, a central computer located in thevehicle along with processor 118. The central computer may determine thecurrent driving environment using the techniques described above withrespect to processor 118. Similarly, processor 118 may additionally oralternatively receive the input from a remote system. For example,processor 118 may receive an indication of the weather from a weatherserver or other source of updated weather information. Similarly,processor 118 may receive an indication of the traffic from a trafficserver or other source of updated traffic information.

In some embodiments, processor 118 may receive the input indicative ofthe current driving environment from at least one of a GPS, a vehiclenavigation system, a vehicle controller, a radar, a LIDAR, and a camera.For example, as explained above, processor 118 may use the vehicle'slocation as determined by the GPS and/or the vehicle navigation systemin combination with maps and/or traffic information to derive thecurrent driving environment. In such an example, processor 118 may alignthe vehicle's GPS location with a map to determine that the vehicle ison an interstate or may align the vehicle's GPS location with trafficinformation to determine that the vehicle is in a traffic jam.Similarly, processor 118 may use the speed, heading, or the like fromthe vehicle controller to derive the current driving environment, asexplained above. Additionally or alternatively, processor 118 may useinformation from radar, LIDAR, and/or a camera to derive the currentdriving environment. For example, processor 118 may identify one or moreobjects using radar, LIDAR, and/or a camera, such as fields, trees,buildings, medians, or the like, and use the identified objects toderive the current driving environment.

At step 4107, based on the current detected or inferred drivingenvironment, processor 118 may coordinate the control of the at leastone light source with the control of the at least one light deflector todynamically adjust an instantaneous detection distance by varying anamount of light projected and a spatial light distribution of lightacross the scan of the field of view. For example, processor 118 mayincrease the amount of light projected and/or decrease the spatialdistribution of light to increase the instantaneous detection distance.By way of further example, processor 118 may decrease the amount oflight projected and/or increase the spatial distribution of light todecrease the instantaneous detection distance. For example, processor118 may determine when the vehicle exits a tunnel and coordinate controlof the at least one light source and the at least one light deflector inorder to increase light emission in at least one portion of the field ofview as compared to a light emission used in the at least one portionwhen the vehicle was in the tunnel, as depicted in the examples of FIGS.42D and 42E.

Processor 118 may vary an amount of light projected across the scan ofthe field of view by varying a length of pulses from the at least onelight source, an amplitude and/or frequency of pulses from the at leastone light source, or the like. Additionally or alternatively, processor118 may vary a spatial light distribution of light across the scan ofthe field of view by varying a strength of the at least one lightdeflector (in embodiments in which, for example, the at least one lightdeflector is piezoelectric or thermoelectrical), an angle of reflectionof the at least one light deflector (e.g., resulting in more or lessspread of a light beam from the at least one light source), or the like.

Processor 118 may base the dynamic adjustment of an instantaneousdetection distance on the current driving environment. For example,processor 118 may increase a detection distance in a rural environment.A rural environment may have objects that are sparser than in an urbanenvironment and, thus, a longer detection distance may compensate forthe increased sparseness. By way of further example, processor 118 maydecrease a detection distance in a traffic jam. A traffic jam may resultin significantly slower speeds and more frequent and sudden stops, thusrendering detection of farther away objects less important. The energynot spent for longer detection ranges may simply be saved, or may beused to improve other detection characteristics, such as resolution,frame rate, SNR, etc.

At step 4107, processor 118 may additionally or alternatively adjustother properties of the LIDAR system. For example, processor 118 maycoordinate the control of the at least one light source with the controlof the at least one light deflector to dynamically adjust a scan rate byvarying an amount of light projected and a spatial light distribution oflight across the scan of the field of view. In such an example,processor 118 may increase a scan rate in an urban environment. An urbanenvironment may have a significant number of other vehicles andpedestrians that are moving and thus, a faster scan rate may allow forearlier detection of events such as stopping of other vehicle ahead ofthe vehicle and movement of pedestrians into a road. By way of furtherexample, processor 118 may decrease a scan rate in a rural environment.A rural environment may have less other vehicles and less pedestriansthan an urban environment, reducing the need for fast scan rates.Accordingly, processor 118 may determine when the vehicle is in an urbanarea and coordinate control of the at least one light source control andthe at least one light deflector in order to cause an increase rate ofscanning cycles as compared to a rate of scanning cycles used in anon-urban area.

In another example, processor 118 may coordinate the control of the atleast one light source with the control of the at least one lightdeflector to dynamically adjust a spatial resolution by varying anamount of light projected and a spatial light distribution of lightacross the scan of the field of view. In such an example, processor 118may increase a spatial resolution in rain. An urban environment may haveobjects that are denser than in an urban environment and, thus, agreater spatial resolution may compensate for the increased density. Byway of further example, processor 118 may decrease a scan rate in atunnel. A tunnel may have little detail besides other vehicles ahead ofthe vehicle, reducing the need for high resolution.

In yet another example, processor 118 may coordinate the control of theat least one light source with the control of the at least one lightdeflector to dynamically adjust a temporal resolution by varying anamount of light projected and a spatial light distribution of lightacross the scan of the field of view. In such an example, processor 118may increase temporal resolution in an urban environment. An urbanenvironment may have a significant number of other vehicles andpedestrians that are moving and thus, a greater temporal resolution mayallow for more detailed monitoring of the movement of other vehicles andpedestrians. By way of further example, processor 118 may decrease atemporal resolution in a rural environment. A rural environment may haveless other vehicles and less pedestrians than an urban environment,reducing the need for detailed monitoring.

In still another example, processor 118 may coordinate the control ofthe at least one light source with the control of the at least one lightdeflector to dynamically adjust a signal-to-noise ratio by varying anamount of light projected and a spatial light distribution of lightacross the scan of the field of view. In such an example, processor 118may increase the signal-to-noise ratio in the rain. Rain may increasethe noise within the environment by increasing the amount of reflectionsin the field of view and thus, a higher signal-to-noise ration mayreduce the impact of the increased noise. By way of further example,processor 118 may decrease the signal-to-noise ratio at night. Noise maydecrease at night, reducing the need for obtaining a stronger signal todifferentiate from the noise.

In an additional example, processor 118 may coordinate the control ofthe at least one light source with the control of the at least one lightdeflector to dynamically adjust a size of the field of view by varyingan amount of light projected and a spatial light distribution of lightacross the scan of the field of view. In such an example, processor 118may decrease the size of the field of view in a rural environment. Arural environment may have roads with fewer lanes, reducing the need fora larger field of view. By way of further example, processor 118 mayincrease the size of the field of view on an interstate. An interstatemay have a large number of lanes and thus, a larger field of view mayallow for monitoring of the large number of vehicles that the interstatemay accommodate.

In a further example, processor 118 may coordinate the control of the atleast one light source with the control of the at least one lightdeflector to dynamically adjust one or more pulse transmission schemesby varying an amount of light projected and a spatial light distributionof light across the scan of the field of view. For example, some schemesmay be more or less susceptible to noise and/or ambient light.Accordingly, processor 118 may select a pulse transmission scheme lesssusceptible to noise in high noise environments such as rain or snow andmay select a pulse transmission scheme less susceptible to ambient lightin environments with high ambient light such as urban environments or atnight.

In embodiments in which the field of view has a plurality of portions,processor 118 may dynamically adjust the instantaneous detectiondistance in the single scanning cycle, such that a detection distance ina first portion of the field of view is increased from a prior scanningcycle and a detection distance in a second portion of the field of viewis decreased from the prior scanning cycle. For example, processor 118may decrease a detection distance in a portion of the field of view infront of the vehicle on a current side of the road and increase adetection distance in another portion of the field of view next to thevehicle and having the other side of the road if the vehicle is in atraffic jam but the other side of the road is not. In such an example,the increased detection distance in the portion containing the otherside of the road may allow for the vehicle to react earlier if a vehicleon the other side of the road is encroaching on the current side.Moreover, the decreased detection distance in the portion containing thecurrent side may prevent needlessly expending energy because traffic isnot moving.

Similarly, processor 118 may dynamically adjust another property of thescan such that the property in a first portion of the field of view isincreased from a prior scanning cycle and the property in a secondportion of the field of view is decreased from the prior scanning cycle.For example, processor 118 may increase a spatial resolution in thefirst portion and decrease a spatial resolution in the second portion.In such an example, processor 118 may increase a spatial resolution fora front portion and decrease a spatial resolution for a side portion ifthe vehicle is in a tunnel. The increased spatial resolution may allowfor the greater tracking of the motion of other vehicles in front of thevehicle, and the decreased spatial resolution may prevent needlesslyexpending energy on tracking the walls of the tunnel.

By way of additional example, processor 118 may increase a temporalresolution in the first portion and decrease a temporal resolution inthe second portion. In such an example, processor 118 may increase atemporal resolution for a side portion and decrease a temporalresolution for a front portion if the vehicle is on an interstate. Theincreased spatial resolution may allow for the more detailed tracking ofthe motion of other vehicles traveling in the opposite direction thatmay necessitate a rapid response if they cross into the vehicle's lane,and the decreased temporal resolution may prevent needlessly expendingenergy on tracking other vehicles in front of the vehicle and travelingwith it.

In another example, processor 118 may increase a signal-to-noise ratioin the first portion and decrease a signal-to-noise ratio in the secondportion. In such an example, processor 118 may increase asignal-to-noise ratio for a side portion and decrease a signal-to-noiseratio for a front portion if the vehicle is in an urban environment. Theincreased signal-to-noise ratio may compensate for ambient light fromstreet lights on the side of a road, and the decreased signal-to-noiseratio may prevent needlessly expending energy on tracking other vehiclesin front of the vehicle and traveling with it.

In yet a further example, processor 118 may increase a size of the firstportion of the field of view and decrease a size of the second portionof the field of view. In such an example, processor 118 may increase thefield of view in a front portion and decrease a field of view for a sideportion if the vehicle is in a rural environment. The increased field ofview may allow for sooner visibility of an oncoming or precedingvehicle, and the decreased field of view may prevent needlesslyexpending energy on tracking fields or trees on the side of the road.

In another example, processor 118 may modify a pulse-transmission schemein the first portion and differently modify a pulse-transmission schemein the second portion. In such an example, processor 118 may select apulse-transmission scheme that minimizes noise for a front portion andselect a pulse-transmission scheme more susceptible to noise for a sideportion if the vehicle is in a rural environment at night. The formerscheme may account for noise from bright headlights of oncoming vehiclesor from rear lights of preceding vehicles, and the latter scheme mayprevent needlessly expending energy on minimizing the already minimalnoise from objects on the side of the road.

Similarly, in some embodiments, processor 118 may, based on the currentdriving environment, coordinate control of the at least one light sourceand the at least one light deflector in a plurality of scanning cyclesto dynamically adjust a first rate of scanning cycles for detectingobjects in a near-field portion of the field of view and a second rateof scanning cycles for detecting objects in a far-field portion of thefield of view. For example, processor 118 may scan objects in anear-field portion at a greater rate than objects in a far-fieldportion. This may allow processor 118 to track the motion of nearerobjects more precisely than the motion of farther objects.Alternatively, processor 118 may scan objects in a near-field portion ata lower rate than objects in a far-field portion.

Method 4100 may include additional steps. For example, method 4100 mayfurther include coordinating control of the at least one light sourceand the at least one light deflector in at least one scanning cycle todynamically adjust an instantaneous point resolution associated with afirst portion of the field of view. For example, a light beam from theat least one light source may be spread across a larger area to producedata across a greater number of pixels or may be compacted into asmaller area to produce data across a smaller number of pixels.

Method 4100 may further include controlling the at least one lightsource based on an environment type corresponding to the received inputindicative of the current driving environment. For example, processor118 may adjust a property of the at least one light source, such as thelight flux, the wavelength, or the like. In such an example, processor118 may select a lower wavelength at night than during the day or mayselect a greater intensity in a rural environment than an urbanenvironment.

Method 4100 may further include adjusting a sensitivity mode of at leastone sensor based on the current driving environment. For example,processor 118 may determine when the vehicle drives in rain and adjust asensitivity mode associated with output from at least one sensor todismiss reflections of rain drops. As discussed above in greater detail,modification of the sensor sensitivity may be achieved by modifyingsensor parameter (e.g., operational voltage), detection-path parameters(e.g., signal amplification level, ADC parameters), or even processorparameters (e.g., processor applied threshold or decision rules).

FIG. 41B illustrates an example method 4100′ for altering detectiondistance in a LIDAR system. Method 4100′ may be performed by at leastone processor (e.g., processor 118 of processing unit 108 of LIDARsystem 100 as depicted in FIG. 1A and/or two processors 118 ofprocessing unit 108 of the LIDAR system depicted in FIG. 2A).

Steps 4101, 4103, and 4105 of method 4100′ of FIG. 41B are the same assteps 4101, 4103, and 4105 of method 4100 of FIG. 41A. Accordingly,their description will not be repeated here.

At step 4107, based on the current detected or inferred drivingenvironment, processor 118 may coordinate the control of the at leastone light source with the control of the at least one light deflector tomodify a detection operational scheme. For example, as explained abovewith reference to FIG. 17, processor 118 may alter an operationalparameter of the at least one sensor and/or processor 118. For example,alteration of the operational parameter in such cases may change thesensitivity of the detection to the signal level and/or noise levelacquired by the at least one sensor. For example, processor 118 mayalter the sensor sensitivity by changing a post-convolution threshold,as discussed above with reference to FIG. 17. However, other operationalparameters of the at least one sensor and/or processor 118 mayadditionally or alternatively be altered by processor 118.

Examples of differing driving environments are depicted in FIGS.42A-42E. In the example of FIG. 42A, a vehicle 4201 may comprise avehicle body and at least one processor located within the vehicle body.The at least one processor may execute method 4100 of FIG. 41 or avariation thereof. In the example of FIG. 42A, vehicle 4201 is drivingin an urban environment. Accordingly, a LIDAR system of vehicle 4201 mayscan field of view 4203 with a higher frame rate (e.g., 25 frames persecond (FPS)), at a moderate distance (e.g., 100 meters), and with awide horizontal field-of-view (e.g., 320°, 340°, 360°, etc.), asdepicted in FIG. 42A. This may account for the moderate speed, highdetail, near objects, and possible rapid change of conditions associatedwith the urban environment.

In the example of FIG. 42B, a vehicle 4205 may comprise a vehicle bodyand at least one processor located within the vehicle body. The at leastone processor may execute method 4100 of FIG. 41 or a variation thereof.In the example of FIG. 42B, vehicle 4205 is driving in a ruralenvironment. Accordingly, a LIDAR system of vehicle 4205 may scan fieldof view 4207 with a moderate frame rate (e.g., 20 frames per second(FPS)), at a larger distance (e.g., 200 meters), and with a moderatehorizontal field-of-view (e.g., 200°, 150°, 120°, etc.), as depicted inFIG. 42B. In some embodiments, the range may be varied over scans, e.g.,scanning at 100 meters for most scans but at 200 meters every fifthscan. Such settings may account for the fast speed, low detail, farobjects, and slower change of conditions associated with the ruralenvironment.

In the example of FIG. 42C, a vehicle 4209 may comprise a vehicle bodyand at least one processor located within the vehicle body. The at leastone processor may execute method 4100 of FIG. 41 or a variation thereof.In the example of FIG. 42C, vehicle 4209 is driving in a traffic jam.Accordingly, a LIDAR system of vehicle 4209 may scan field of view 4211with a moderate frame rate (e.g., 20 frames per second (FPS)), at ashort distance (e.g., 75 meters), and with a moderate horizontalfield-of-view (e.g., 200°, 150°, 120°, etc.), as depicted in FIG. 42C.Such settings may account for the low speed, low detail, close objects,and generally slower change of conditions associated with a traffic jam.

In the example of FIG. 42D, a vehicle 4213 may comprise a vehicle bodyand at least one processor located within the vehicle body. The at leastone processor may execute method 4100 of FIG. 41 or a variation thereof.In the example of FIG. 42D, vehicle 4213 is driving through a tunnel.Accordingly, a LIDAR system of vehicle 4213 may scan field of view 4215using different properties in regions 4217 a and 4217 c than in regions4217 b. In regions 4217 a and 4217 c, a low frame rate (e.g., 10 framesper second (FPS)), a short distance (e.g., 75 meters), and a low spatialand/or temporal resolution may be used to account for the lack ofnecessity in tracking the walls of the tunnel. On the other hand, inregion 4217 b, a moderate frame rate (e.g., 20 frames per second (FPS)),a moderate distance (e.g., 100 meters), and a moderate spatial and/ortemporal resolution may be used to track possible sudden stopping ofanother vehicle preceding vehicle 4213. Alternatively, as depicted inFIG. 42D, regions 4217 a and 4217 c may not be scanned (as depicted bythe “X”) while region 4217 b is scanned.

In the example of FIG. 42E, vehicle 4213 is now exiting the tunnel.Accordingly, a LIDAR system of vehicle 4213 may scan field of view 4215′using different properties in regions 4217 a′ and 4217 c′ thanpreviously used in regions 4217 a and 4217 c. For example, the framerate, detection distance, and/or spatial and/or temporal resolution maybe increased to account for the necessity of tracking possible objectsin those regions. On the other hand, frame rate, detection distance,and/or spatial and/or temporal resolution in region 4217 b′ may be keptthe same as those used in region 4217 b. Alternatively, regions 4217 aand 4217 c may now be scanned in addition to region 4217 b, either withthe same properties (as depicted in FIG. 42E) or with differingproperties.

FIG. 42F depicts vehicles 4201, 4205, and 4209 of FIGS. 42A, 42B, and42C, respectively, with their corresponding fields of view 4203, 4207,and 4211. As depicted in FIG. 42F, field of view 4203 for vehicle 4201in an urban environment has a moderate detection distance and a widehorizontal field-of-view. As further depicted in FIG. 42F, field of view4207 for vehicle 4205 in a rural environment has a larger detectiondistance than field of view 4203 (in the urban environment) but has amoderate horizontal field-of-view compared with field of view 4203 (inthe urban environment). As still further depicted in FIG. 42F, field ofview 4211 for vehicle 4209 in a traffic jam has a shorter detectiondistance than field of view 4203 (in the urban environment) but also hasa wide horizontal field-of-view (e.g., similar to that of field of view4203 in the urban environment).

Additional driving environments not depicted in FIGS. 42A-42F may resultin adjustments of one or more properties of the LIDAR system. Forexample, in the rain, a LIDAR system consistent with embodiments of thepresent disclosure may scan a field of view with a higher frame rate(e.g., 25 frames per second (FPS)) and higher spatial and/or temporalresolution to accommodate for the greater noise and distorted detail ineach frame.

FIG. 43 is a diagram illustrating an example LIDAR system 4300 having aplurality of light sources aimed at a common area of at least one lightdeflector. As depicted in FIG. 43, light from the plurality of lightsources may impinge on an overlapping area of the at least one lightdeflector. Additionally or alternatively, light originating from theplurality of light sources and reflected back from the scene may impingeon an overlapping area of the at least one light deflector. As depictedin FIG. 43, system 4300 includes a processing unit (e.g., at least oneprocessor 4301) along with a plurality of light sources (e.g., lightsources 4303 a. 4303 b, and 4303 c). The plurality of light sources 4303a, 4303 b, and 4303 c may emit a corresponding plurality of light beams(e.g., light beams 4305 a, 4305 b, and 4305 c).

In the embodiment of FIG. 43, LIDAR system 4300 includes at least onedeflector 4309 having a common area 4307. At least one deflection 4309may, for example, be in a particular instantaneous position during ascan cycle. The plurality of light sources 4303 a, 4303 b, and 4303 cmay be aimed at common area 4307 and thus direct the plurality ofcorresponding light beams 4305 a, 4305 b, and 4305 c thereto. Commonarea 4307 may project the plurality of light beams 4305 a, 4305 b, and4305 c to a field of view 4311. In the embodiment of FIG. 43, commonarea 4307 may project the plurality of light beams 4305 a, 4305 b, and4305 c towards a plurality of independent regions (e.g., regions 4313 a,4313 b, and 4313 c) that form the field of view 4311. The plurality oflight beams 4305 a, 4305 b, and 4305 c cause a plurality ofcorresponding reflections 4315 a, 4315 b, and 4315 c from field of view4311 (or from objects therein).

Furthermore, in the example of FIG. 43, the scanning rates for theplurality of regions 4313 a, 4313 b, and 4313 c may differ. For example,as depicted in FIG. 43, the scan rate for region 4313 a may be slowerthan that of region 4313 b, and the scan rate of region 4313 c may be

In other embodiments, additional or alternative properties of the scanmay differ between the plurality of regions 4313 a, 4313 b, and 4313 c.For example, an instantaneous detection distance, a spatial resolution,a temporal resolution, a signal-to-noise ratio, a size of the field ofview, one or more pulse-transmission schemes, or the like mayindependently or in combination differ between the plurality of regions4313 a, 4313 b, and 4313 c.

In the example of FIG. 43, both light beams 4305 a, 4305 b, and 4305 cand corresponding reflections 4315 a, 4315 b, and 4315 c both hit commonarea 4307 of at least one deflector 4309. In other embodiments, however,light beams 4305 a, 4305 b, and 4305 c may be projected by one or moredifferent deflectors than those by which corresponding reflections 4315a, 4315 b, and 4315 c are reflected.

As further depicted in the example of FIG. 43, each reflection 4315 a,4315 b, and 4315 c is directed to a corresponding at least one deflectorand sensor (e.g., deflectors 4317 a, 4317 b, and 4317 c correspondinglycoupled with sensors 4319 a, 4319 b, and 4319 c). In other embodiments,however, any additional deflectors may be omitted. In addition, in otherembodiments, more than one reflection may be directed to a singlesensor.

Lidar Detection Scheme for Cross Traffic Turns

Cross-lane turns without can present certain challenges. For example,navigating a vehicle along a path that crosses one or more lanes oftraffic (e.g., turning left at an intersection in the United States orturning right at a junction in England, etc.), can be difficult in heavytraffic with oncoming vehicles, bicycles, and pedestrians. Human driversmay enter the intersection and wait for an opportunity to accelerate andperform the risky cross-lane turn. Similar challenges may exist forautonomous or semi-autonomous vehicles.

To aid in navigating an intersection or other road situation thatincludes crossing a lane of traffic, LIDAR system 100 may be configuredto alter one or more operational characteristics of the system relativeto certain regions of the LIDAR FOV, as compared to other regions of theLIDAR FOV. For example, in a LIDAR system consistent with embodiments ofthe present disclosure, a detection range of a certain region of theLIDAR FOV (e.g., a portion of the FOV overlapping with a lane to becrossed) may be increased relative to one or more other regions of theLIDAR FOV. For example, in one example, if a vehicle (autonomous orotherwise) is attempting to make a left turn across at least one lane oftraffic, a detection range associated with one or more regions of theLIDAR FOV overlapping the lanes to be crossed (e.g., generally on aright half of the FOV, which may correspond to a right forward quarterof the vehicle that faces the oncoming traffic of the lane to becrossed) may be extended to exceed a detection range in other regions ofthe FOV (e.g., generally on a left half of the FOV, which may correspondto a left forward quarter of the vehicle not facing the oncoming trafficof the lane to be crossed). It should be noted that a LIDAR FOV mayinclude the aggregate of multiple scanning regions, whether contiguousor not. For example, in some embodiments, a LIDAR FOV may be made up ofa plurality of portions that overlap continuous range of solid anglevalues. In other embodiments, the LIDAR FOV may be an aggregate ofmultiple non-overlapping or partially overlapping solid angle rangeseach being bisected by an axis extending in a different direction (e.g.,as shown in FIG. 45). In this manner, LIDAR system 100 may be betterable to detect oncoming vehicles and to generate higher resolution depthmaps associated with the lanes to be crossed.

Systems and methods of the present disclosure may allow a detectionrange in a direction opposing the direction of the cross-lane turn(e.g., a detection range associated with one or more regions of the FOVon a right half of the FOV when a direction of the cross-lane turn is tothe left) of the vehicle to temporarily exceed a detection range towarda direction of the cross-lane turn. Such a change in the detection rangemay be made, for example, by coordinating the control of at least onelight source with the control of at least one light deflector toincrease light flux, relative to other portions of the field of view, ona side of the vehicle opposite a direction of the cross-lane turn andencompassing a far lane of traffic into which the vehicle is merging.

FIG. 44 illustrates an example method 4400 for a LIDAR detection schemefor cross traffic turns. Method 4400 may be performed by at least oneprocessor (e.g., processor 118 of processing unit 108 of LIDAR system100 as depicted in FIG. 1A and/or two processors 118 of processing unit108 of the LIDAR system depicted in FIG. 2A). At step 4401, processor118 controls at least one light source (e.g., light source 112 of FIG.1A, laser diode 202 of light source 112 of FIG. 2A, and/or plurality oflight sources 102 of FIG. 2B) in a manner enabling light flux of lightfrom at least one light source to vary over a scanning cycle of a fieldof view (e.g., field of view 120 of FIGS. 1A and 2A). For example,processor 118 may vary the timing of pulses from the at least one lightsource. Alternatively or concurrently, processor 118 may vary the lengthof pulses from the at least one light source. By way of further example,processor 118 may alternatively or concurrently vary a size (e.g.,length or width or otherwise alter a cross-sectional area) of pulsesfrom the at least one light source. In a yet further example, processor118 may alternatively or concurrently vary the amplitude and/orfrequency of pulses from the at least one light source.

Step 4402 may further include processor 118 controlling at least onedeflector (e.g., light deflector 114 of FIG. 1A, deflector 114A and/ordeflector 114B of FIG. 2A, and/or one-way deflector 214 of FIG. 2B) todeflect light from the at least one light source in order to scan thefield of view. For example, processor 118 may cause mechanical movementof the at least one light deflector to scan the field of view.Alternatively or concurrently, processor 118 may induce a piezoelectricor thermoelectrical change in the at least one deflector to scan thefield of view.

In some embodiments, a single scanning cycle of the field of view mayinclude moving the at least one deflector such that, during the scanningcycle, the at least one light deflector is located in a plurality ofdifferent instantaneous positions (e.g., the deflector is controlledsuch that the deflector moves from or through one instantaneous positionto another during the scan of the LIDAR FOV). For example, the at leastone light deflector may be moved continuously or non-continuously fromone of the plurality of positions to another (optionally with additionalpositions and/or repetitions) during the scanning cycle.

In such embodiments, processor 118 may coordinate the at least one lightdeflector and the at least one light source such that, when the at leastone light deflector is located at a particular instantaneous position, alight beam is deflected by the at least one light deflector from the atleast one light source towards the field of view and reflections from anobject in the field of view are deflected by the at least one lightdeflector toward at least one sensor. Accordingly, the at least onelight deflector may direct a light beam toward the field of view andalso receive a reflection from the field of view. For example, FIGS. 1A,2B, and 2C depict examples in which a deflector both directs a lightbeam towards the field of view and also receives a reflection from thefield of view. In certain aspects, the reflection may be caused by thelight beam directed toward the field of view. In other embodiments, alight beam from the at least one light source may be directed towardsthe field of view by at least one light deflector separate from at leastone other light deflector that receives a reflection from the field ofview. For example, FIG. 2A depicts an example in which one deflectordirects a light beam towards the field of view and a separate deflectorreceives a reflection from the field of view.

At step 4403, processor 118 obtains input indicative of an impendingcross-lane turn of the vehicle. Examples of cross-lane turn techniquesare discussed below with references to FIGS. 45 and 46.

At step 4404, in response to the input indicative of the impendingcross-lane turn, processor 118 may coordinate the control of the atleast one light source with the control of the at least one lightdeflector to increase light flux, relative to other portions of thefield of view, on a side of the vehicle (i.e., a direction, angle,region of interest, and not a part of the vehicle) opposite a directionof the cross-lane turn and encompassing a far lane of traffic into whichthe vehicle is merging, and causing a detection range opposing thedirection of the cross-lane turn of the vehicle to temporarily exceed adetection range toward a direction of the cross-lane turn.

In some embodiments, processor 118 may control one light source or onelight deflector to increase light flux, relative to other portions ofthe field of view, on a side of the vehicle opposite a direction of thecross-lane turn and encompassing a far lane of traffic into which thevehicle is merging. For example, if the deflector (e.g., light deflector114 of FIG. 1A, deflector 114A and/or deflector 114B of FIG. 2A, and/orone-way deflector 214 of FIG. 2B) continues scanning according to afixed scan schedule, parameters of light source 112 may be changed inorder to vary a detection range in regions of the LIDAR FOV whereobjects (e.g., vehicles) in one or more of the lanes of traffic to becrossed by the cross-lane turn may be found. Such regions of the FOVwhere a detection range may be increased (either individually or in theaggregate) may be referred to as regions of interest.

In some embodiments, a detection range in a region of interest may behigher than a detection range in regions of the FOV outside the regionof interest. Any suitable ratio of detection ranges may be accomplished.In some embodiments, a detection range in a region of interest may be atleast two times greater than a detection range outside a region ofinterest. In a particular example in the context of a vehicle making across-lane turn, processor 118 may detect a vehicle at range X in adirection corresponding to a region of interest (e.g., a particularportion of the LIDAR FOV overlapping with the cross-lane) and may becapable of detecting vehicles only at a range of X/2 or less in a regionof the LIDAR FOV not in a region of interest (e.g., not overlapping withthe cross-lane). For example, if an autonomous vehicle is preparing to,initiating, and/or making a left turn, the region of interest may be inthe right half of the LIDAR FOV, which may encompass at least a portionof the right side of the vehicle. In some cases, the region of the LIDARFOV overlapping with an area immediately forward of the vehicle may falloutside of the region of interest. Additionally or alternatively a LIDARsystem FOV may be provided across different segments, each segmentpotentially being directed to a different zone surrounding a vehicle,for example. In such cases, the region of interest of the LIDAR FOV mayreside on the passenger side of the vehicle, the driver side of thevehicle, at the rear of the vehicle, in any quartering directionrelative to the vehicle (e.g., between a longitudinal and a lateral axisthrough the vehicle), etc. Processor 118 may control light source 112(including any of its controllable parameters affecting light output)and deflector 114, among other components of LIDAR system 100, in amanner to increase the detection range in region of interest and toconserve resources relative to regions of the LIDAR FOV of lowerinterest.

Method 4400 may include additional steps. For example, method 4400 mayfurther include controlling the light deflector such that during ascanning cycle of the field of view the at least one light deflector islocated in a plurality of different instantaneous positions.Alternatively, method 4400 may further include coordinating at least onelight deflector and at least one light source such that when the lightdeflector is located at a particular instantaneous position, a portionof a light beam is deflected by the light deflector from the lightsource towards an object in the field of view, and reflections of theportion of the light beam from the object are deflected by the lightdeflector toward at least one sensor. In some embodiments, the LIDARsystem may further comprise a plurality of light sources aimed at the atleast one light deflector. The processor may control the light deflectorsuch that when the light deflector is located at a particularinstantaneous position, light from the plurality of light sources isprojected towards a plurality of independent regions in the field ofview.

Processor 118 may determine that a host vehicle is planning to execute across-lane turn or has initiated a cross-lane turn based on varioussources. For example, in some embodiments, processor 118 may receive aninput indicative of an impending cross-lane turn from a navigationsystem of the vehicle. In other embodiments, processor 118 may receivean input indicative of the impending cross-lane turn from another systemof the vehicle (e.g., one or more sensors, engaged turn signals, wheelsteering direction, GPS sensor, etc.) or a system external to thevehicle (e.g., one or more autonomous vehicle navigation server systems,mapping systems, etc.). In other embodiments, processor 118 maydetermine the input indicative of the impending cross-lane turn based oninformation received from at least one sensor (e.g., sensor 116)configured to detect reflections associated with the light projectedfrom the at least one light source. In other words, processor 118 maydetermine an impending or initiated cross-lane turn based on an outputof sensor 116 of the LIDAR system 100.

Processor 118 may be configured to determine one or more characteristicsof objects detected within a lane to be crossed. In some cases, the oneor more characteristics may include a distance to a detected objectand/or a type of object (e.g., car, truck, stationary object,pedestrian, etc.). In some embodiments, processor 118 may also determinea velocity of a moving object detected in the cross lane (e.g., a farlane of traffic), a direction of travel (e.g., by monitoring a locationover two or more scans of the FOV), or any other characteristicassociated with a detected object. In some embodiments, processor 118may monitor motion characteristics of the host vehicle (e.g., velocity,acceleration, position, etc.) and may determine based on motioncharacteristics of the host vehicle and motion characteristics of adetected object (e.g., in a cross-lane) to determine if the host vehicleand the detected object are on a collision course. If so, processor 118may trigger an alert (e.g., a horn blast, visual alert, wirelesscommunication to a controller associated with the detected object, etc.)if the host vehicle and the moving object are determined to be on acollision course. In other embodiments, a determination of a collisioncourse may include other potential hazards. For example, even if thehost vehicle is stationary, an alert to the host may be issued if, forexample, an approaching vehicle poses a hazard to the host vehicle inits current position or where the host vehicle expects to move. In someembodiments, processor 118 may cause alerts to be issued (audible,visual, or otherwise) not only in an autonomous mode, but also in othermodes (e.g., advanced driver assist system operation, full drivercontrol, etc.).

In some embodiments, processor 118 may generate a reflectivity imageassociated with the LIDAR field of view. The reflectivity image mayinclude a fingerprint of a detected moving object representing an amountof light reflected from various portions of the moving object. By way ofexample, when light from light projector 112 is incident on objects inan environment of LIDAR system 100, based on the reflectivitycharacteristics of those objects, processor 118 can detect a pattern.For example, processor 118 may identify a reflectivity pattern orfingerprint in order to determine a type category associated with thedetected object (e.g., a pedestrian, vehicle, road divider barrier,etc.). Processor 118 may also be able to determine a sub-type associatedwith the detected object (e.g., whether a detected vehicle is a bus, asmall car, or a van, etc.). Every vehicle may exhibit a differentreflectivity fingerprint based on its shape and its configuration (e.g.,license plate location and surrounding contours; headlight size, shape,spacing, and placement on a vehicle; etc.).

In some embodiments, processor 118 may be configured to determined oneor more states of a detected object based on a comparison between adetected reflectivity pattern and a predetermined reflectivitytemplates. For example, in some embodiments, processor 118 may compareone or more reflectivity fingerprints acquired relative to a detectedmoving object (e.g., over a plurality of scanning cycles) with aplurality of predetermined/stored reflectivity templates to determinethat the moving object is a vehicle signaling a right turn.

Processor 118 may also be configured to allocate different light fluxlevels to different regions of the LIDAR FOV based on detected maneuversby the host vehicle. For example, in some embodiments, processor 118 mayapply a differing power allocation scheme for right turns than for leftturns. For example, depending on the change in light flux, processor 118may allocate different power for a left turn than for a right turn.Additional examples of power budget allocation are further describedrelative to FIGS. 29-31.

In yet other embodiments, processor 118 may receive input indicative ofa current driving environment and apply a different power allocationschemes depending on the determined driving environment. For example,processor 118 may apply different power allocation schemes forcross-lane turns in a rural area than for cross-lane turns in an urbanarea. By way of example, in an urban area, there may be a greaterlikelihood that pedestrians or bicyclists may approach the host vehiclefrom sides of the vehicle. Accordingly, there may be a greater need inan urban area, as compared to a more rural area, to detect objects inone or more directions relative to the host vehicle (e.g., driver side,passenger side, rear, etc.) with more precision than when in a ruralarea. In a rural area, by contrast, fewer pedestrians and otherobstacles may be present. Thus, there may be less need for highresolution depth maps around the host vehicle, especially at distanceranges close to the host vehicle. On the other hand, however, vehiclespeed in rural environments tends to be higher than in an urban area dueto various factors, including less traffic. As a result, processor 118may allocate fewer resources to detection of objects in close proximityto the host vehicle (e.g., within about 40 m, 20 m, etc.) and instead,may allocate more resources to detection of objects that are moredistant.

In some embodiments, processor 118 may control at least two lightsources and at least two deflectors to enable scanning a first field ofview associated with a right side of the vehicle and a second field ofview associated with a left side of the vehicle. In yet otherembodiments, processor 118 may control the at least one light source 112such that an amount of light projected toward a first portion of thefield of view including a road onto which the vehicle is merging isgreater than an amount of light provided to a second portion of thefield of view including a building adjacent the road.

As previously described, increases in light flux provided to particularportions of the LIDAR FOV may enhance detection capabilities, amongother capabilities, in those regions, the field of view (e.g., field ofview 120 of FIGS. 1A and 2A) may be enlarged. As described in FIG. 2C,primary light source 112A may project light with a longer wavelength inorder to optimize detection range. As further described in FIG. 5A, thetime between light pulses may depend on desired detection range.Specifically, sending the same amount light pulses in a shorter periodof time may increase light flux. As described in FIG. 5C, varying thenumber of pulses or changing the amount of time between pulses may notbe the only ways to adjust light flux. Changes in light flux may also beimplemented in other ways such as: pulse duration, pulse angulardispersion, wavelength, instantaneous power, photon density at differentdistances from light source 112, average power, pulse power intensity,pulse width, pulse repetition rate, pulse sequence, pulse duty cycle,wavelength, phase, polarization, and more.

By way of example, processor 118 may control at least one light source(e.g., light source 112 of FIG. 1A, laser diode 202 of light source 112of FIG. 2A, and/or plurality of light sources 102 of FIG. 2B) in amanner enabling light flux of light from at least one light source tovary over a scanning cycle of a field of view (e.g., field of view 120of FIGS. 1A and 2A).

FIG. 45 includes a diagram 4500 illustrating an example of a LIDARdetection scanning scheme. As depicted, autonomous vehicle 4510 driveseast to west on a road approaching vehicle 4530 driving west to east.Autonomous vehicle 4510 may including a LIDAR system capable ofprojecting light toward seven different regions of an environmentsurrounding vehicle 4510 to provide seven fields of view (which mayoverlap in at least some portions). In some embodiments, each field ofview of the LIDAR system may be associated with a corresponding modulewhich may a light source 112, a deflector 114, a detector 116, andrelated optics components (e.g., lenses, etc.), although more or fewcomponents may be possible. For simplicity, each of these modules willbe referenced here as a lens system as a means for identifying thedifferent fields of view. Through the lens systems, the LIDAR system mayreceive reflected light from objects in the fields of view. Autonomousvehicle 4510 may have field of view 4521 (e.g., similar to field of view120 of FIG. 1A) corresponding to lens system 4511, field of view 4522corresponding to lens system 4512, field of view 4523 corresponding tolens system 4513, field of view 4524 corresponding to lens system 4514,field of view 4525 corresponding to lens system 4515, field of view 4526corresponding to lens system 4516, and field of view 4527 correspondingto lens system 4517.

In one particular example (not shown), LIDAR system 100 may include fourlens systems that “look” ahead of the car. In total, the four lenssystems may cover an aggregated 160° field of view using four lightsources, each scanning, for example, via a shared deflector a horizontalfield of view of 40°. Processor 118 may, in some embodiments, increaselight flux by a first light source (corresponding to a portion of theFOV in which a cross-lane may be located) while concurrently reducinglight flux for a second light source (corresponding to another directionand an FOV portion not substantially overlapping with a region ofinterest, such as a cross-lane). The reflections of both signals mayimpinge on a common light deflector 114 (e.g. mirror).

FIG. 46A depicts diagram 4600 illustrating an example of LIDAR detectionscheme for cross traffic turns. Autonomous vehicle 4510 of FIG. 45 mayenter an intersection for a cross-lane turn. In other embodiments, theautonomous vehicle may enter a T junction, a Y intersection, or anyother type of intersection/junction for a cross-lane turn. Autonomousvehicle 4510 may follow a path, e.g., trajectory 4620, for thecross-lane turn. As autonomous vehicle 4510 enters the intersection (oreven before), processor 118 may increase light flux levels to a portionof the LIDAR field of view represented by FOV portions 4525, 4522, and4523. A result a potential detection range associated with thoseportions may increase relative to other portions of the total LIDAR FOV.For example, as depicted, FOV portion 4522 may have a detection rangegreater than FOV portion 4521; FOV portion 4523 may have a detectionrange greater than 4524; FOV portion 4525 (the portion on a side of thevehicle facing the oncoming direction of the lane being crossed) mayhave a detection range greater than FOV portion 4526 and may also have adetection range greater than FOV portions 4522 and 4523. In some cases,the detection range of FOV portion 4525 may be more than twice as longas is other FOV portions. As depicted in FIG. 46A, FOV portion 4525, onthe right side of the vehicle, may be allocated the highest light fluxand have the largest detection range during the left cross-lane turnbecause it is in a direction determined to be overlapping with a regionof interest. Detection ranges of FOV portions 4521, 4526, and 4524, onthe left side of the vehicle may remain unchanged relative to theirdefault values (e.g., as shown in FIG. 45 prior to the cross-lane turnshown in FIG. 46A). Alternatively, light flux projected to any of FOVportions 4521, 4526, and 4524, on the left side of the vehicle may bereduced relative to their default values during the cross-lane turn. FOVportion 4527, capturing the front of autonomous vehicle 4510 during thecross-turn situation of FIG. 46A may be allocated with a light fluxlevel lower than a level normally allocated to the forward FOV portionin a non-cross-lane situation. For example, as shown in FIG. 45, FOVportion 4527 may be allocated a higher light flux value, which in turnmay increase the detection range for FOV portion 4527, in situationssuch as a vehicle travelling at speed on a road. A light flux level ofFOV portion 4527 may be reduced in a cross-lane situation as speeds maybe lower than the situation shown in FIG. 45. Also, the side of thevehicle adjacent to oncoming traffic in a cross-lane situation mayrepresent a region of higher interest (e.g., from a potential collisionstandpoint) as compared to a forward travelling direction of the vehiclein the cross-lane situation of FIG. 46A. Of course, as right turns(e.g., in the US and other countries where cars travel on the right sideof the road) may not involve cross-lane situations, it may not benecessary to increase the light flux in FOV portions of the LIDAR systemresiding on a left side of the vehicle. In countries such as Japan andthe UK, however, light flux supplied to FOV portions on the left side ofthe vehicle may be increased during a right turn cross-lane situation.Processor 118 may be equipped to automatically determine a location forthe host vehicle (e.g., based on the output of a vehicle navigationsystem, a GPS sensor, etc.) and control the light flux applied to thevarious FOV portions according to driving customs/road configurations,etc. in the determined location.

As further depicted in FIG. 46A, processor 118 may detect vehicle 4610during the cross-lane turn due to the extended detection range from FOVportion 4525. By way of example, processor 118 may determine whetherdetected object is an object of interest, for example, a moving vehicle,pedestrian, etc. Processor 118 may differentiate between a building, thesidewalk, a parked vehicle, a pedestrian, and a moving vehicle based atleast on the reflectivity pattern associated with the detected object.Accordingly, processor 118 may allocate greater levels of resources toFOV portions determined to include such objects of interest (movingvehicles or pedestrians, etc.) and may conserve resources by reducing(or not increasing) resource expenditures on FOV portions determined tocontain a building, parked car, or other stationary object.

In some embodiments, processor 118 may increase light flux supplied to aparticular sub-region of an FOV portion. For example, in the cross-lanesituation shown in FIG. 46A, moving car 4610 may be determined byprocessor 118 to be an object of interest. Thus, processor 118 may causemore light flux to be provided to sub-regions of FOV portion 4525 thatoverlap with car 4610. Processor 118 may also increase light levelsprovided to one or more sub-regions of an FOV portion in othercircumstances. For example, where no objects are detected or where noobjects beyond a certain distance are detected within a particularsub-region of the FOV portion, processor 118 may allocate increasedlight flux to those sub-regions in an attempt to detect objects at moredistant ranges.

FIG. 46B provides another example of a LIDAR detection scheme for crosstraffic turns. In this example, vehicle 4510 has approached aT-intersection and is stopped and waiting for an opportunity to turnleft into the far lane. In this situation, there may be little risk ofobject encounters from the rear of vehicle 4510 or from much of the leftside of vehicle 4510. Rather, the areas of most interest may be forwardand to the left and right of the vehicle. Thus, light projections toFOVs 4526, 4524, and 4523 may be reduced, as long detection rangesand/or high resolution depth mapping may not be required in these zones.In some embodiments, reduction of light projected to FOVs 4526, 4524,and 4523 may free up resources that may be used relative to other fieldsof view. For example, light emission power and/or computationalresources that would have been used in detecting objects in largerversions of FOVs 4526, 4524, and 4523 may be reallocated to other FOVs,such as FOV 4521, 4522, 4527, or 4525, by reducing the resourcesrequired to scan FOVs 4526, 4524, and 4523.

With more resources available to enhance detection in important areas,LIDAR system 100 may increase an amount of light flux projected to FOV4521 in order to increase a detection range in an area forward and tothe left of vehicle 4510. And the increase in light flux provided to FOV4521 need not be uniform over all regions of the FOV. Rather, as shownin FIG. 46B, FOV 4521 may be segmented into FOV sub-regions 4680 and4682. While both sub-regions may receive more light flux than FOV 4526,for example, sub-region 4680 may receive more light flux than sub-region4682 during one or more scanning cycles of FOV 4526. Such an FOVscanning scheme may potentially increase a detection distance in thelane of traffic approaching from the left.

In making a left turn at the T-intersection shown in FIG. 46B, it may beimportant to enhance detection capabilities with respect to vehiclesapproaching vehicle 4510 from the left. Thus, as described above, morelight flux can be supplied to FOV 4521 and distributed to itssub-regions either uniformly or non-uniformly, as described above, toenhance detection capabilities with respect to vehicles approaching fromthe left. In the situation illustrated in FIG. 46B, however, what may beeven more important is the detection capability of traffic approachingvehicle 4510 from the right. While generally, traffic approaching fromthe left and the right may be expected to approach vehicle 4510 withsimilar velocities, an interaction time with vehicles approaching fromthe right may be significantly longer than interaction times forvehicles approaching from the left. For example, to turn left at theT-intersection shown, vehicle 4510 may need to determine whether anycars are approaching from the right and whether under normalacceleration conditions there is sufficient time for vehicle 4510 simplyto clear in front of left-approaching vehicles. Once clear of thosevehicles, the interaction between vehicle 4510 and a left-approachingvehicle may end.

On the other hand, the interaction time between vehicle 4510 andright-approaching vehicles may be longer, assuming vehicle 4510 ismaking a left turn a the illustrated T-intersection. For example, notonly must vehicle 4510 determine if there is sufficient time to navigatein front of a right-approaching vehicle, but vehicle 4510 must alsodetermine if there will be sufficient time to accelerate up to speedforward of the right-approaching vehicle without that vehicle collidingwith the rear of vehicle 4510 after vehicle 4510 completes the left turnand during its acceleration period. Thus, not only may there be a needfor greater detection ranges to detect vehicles, such as vehicle 4690,approaching from the right, but there may be a need for detection rangesthat are even longer than the detection ranges needed to detectleft-approaching vehicles. Thus, in the example shown, both FOVs 4522and 4525 (the FOVs that have coverage of a region forward and to theright of vehicle 4510) have been allocated with increased light fluxlevels in order to increase detection capabilities forward and to theright of vehicle 4510. Again, such light increases need not be madeuniformly over all regions of the respective FOVs. Rather, asillustrated, a sub-region 4675 of FOV 4525 has been allocated with morelight than another sub-region 4676 of FOV 4525. Indeed, the amount oflight supplied to sub-region 4675 may be significantly more than theamount of light supplied to sub-region 4676. As a result, a detectionrange in sub-region 4675 may be two times, three times, five times, tentimes (or more) greater than a detection range associated withsub-region 4676.

Similarly, increased light levels may be applied to FOV 4522. Asillustrated, FOV 4522 may include three sub-regions, 4677, 4678, and4679, and the light flux levels applied to these sub-regions mayprogressively increase from sub-region 4677 to sub-region 4679, suchthat sub-region 4679 may offer a higher detection range than sub-region4678, which may offer a higher detection range than sub-region 4677. Byreallocating available resources (e.g., an optical budget) in thismanner, a right-approaching vehicle 4690 may be detected at rangessufficient to determine whether vehicle 4510 has enough time to merge infront of vehicle 4690 and accelerate to speed.

Dynamic Illumination Allocation in Highway Driving

LIDAR system 100 may be incorporated onto a vehicle (e.g., onto a bodyof the vehicle or in any other suitable position). And as discussedprevious, LIDAR system 100 may be capable of dynamically controllingamounts of light flux provided to different portions of the LIDAR FOV.In one example, discussed below, processor 118 may determine orotherwise receive an indication that the vehicle is driving along ahighway (e.g., where the vehicle may travel at higher speeds with lessrisk of encountering crossing obstacles, such as pedestrians, bicycles,and other vehicles, which are more typically found in an urbanenvironment, etc.). In response to such an indication, processor 118 mayapportion an available optical budget such that over one or more scansof the LIDAR FOV, more light flux may be provided to a central region ofthe FOV than to peripheral regions of the FOV. Such apportionment oflight flux may be appropriate for highway driving where there may be aneed for increasing a detection range ahead of the vehicle and wherethere may be less need for maintaining long-range or high resolutiondetection capabilities in peripheral regions of the FOV. In instanceswhere processor 118 determines that the host vehicle has left a highwayenvironment and, for example, entered a non-highway road or environment(e.g., an urban environment) where there may be greater risk ofcollision with crossing objects, processor 118 may reapportion theoptical budget such that the extra light flux applied in a centralregion of the FOV during highway driving is reallocated to theperipheral regions.

More specifically, in some embodiments, processor 118 of LIDAR system100 may control at least one light source 112 in a manner enabling lightflux of light from at least one light source to vary over a scanningcycle of the FOV. Processor 118 may also control at least one deflector114 to deflect light from light source 112 in order to scan the FOV,which may be dividable into a central region generally corresponding alocation of a road on which the vehicle travels, a right peripheralregion generally corresponding to an area right of the road, and a leftperipheral region generally corresponding to an area left of the road.Processor 118 may obtain input that the vehicle is in a modecorresponding to highway travel, and in response to the input, processor118 may coordinate control of light source 112 with control of lightdeflector 114 such that during scanning of the FOV, more light may bedirected to the central region than to the right peripheral region andto the left peripheral region.

Processor 118 may receive, from any suitable source, an indication thatthe host vehicle is travelling on a highway. In some cases, thisinformation may be obtained through communication with a vehiclenavigation system 4740 (FIG. 47), via a GPS receiver and a map server ormap application, through analysis of images from one or more cameras,based on an output from LIDAR system 100 itself, based on outputs ofother LIDAR systems, etc. For example, in some embodiments, navigationsystem 4730 may incorporate, access, or otherwise receive from a remoteserver one or more maps from which a status of a roadway as a highway oras a non-highway may be determined. Processor 118 may receive anindication of whether a roadway is a highway directly from navigationsystem 4730. In other cases, processor 118 may determine a roadwaystatus based on one or more indicators associated with map informationused by navigation system 4730 (e.g., a roadway status indicator, aspeed limit associated with a particular road, etc.). In some cases,processor 118 may determine a road status as a highway or non-highwaybased on a combination of information from two or more sensors orinformation sources. For example, in combination with informationreceived from navigational information 4730, processor 118 may receiveposition information from a GPS receiver, speed information from avehicle sensor (e.g., a speedometer), visual information from a camera,depth map information from one or more LIDAR systems (including thesystem in which processor 118 is based), or any other suitable source,and may use a combination of information sources to determine whether aroad being traveled is a highway. Such auxiliary information sources mayconvey information indicative of vehicle speed, vehicle position,identified lane markings, identified landmarks, identified roadbarriers, a direction of traffic flow, a road width, a lane width, laneconfiguration, identified traffic signs, identified traffic lights, etc.Processor 118 may use any of this information alone or in combination toverify a status of a road.

FIG. 47 provides a diagrammatic illustration of a vehicle travelling ina highway environment with the assistance of a LIDAR system consistentwith exemplary disclosed embodiments. Vehicle 4710 may be equipped withLIDAR system 100 and in some cases navigation system 4730. As shown.LIDAR FOV 120 may be partitioned into central region 4720, rightperipheral region 4724, and left peripheral region 4722. By coordinatingoperation of light projector 112 and deflector 114, processor 118 maycause FOV 120 to be scanned during one or more scanning cycles (e.g., bymoving deflector either continuously or discontinuously through aplurality of different instantaneous positions at different times duringa scanning cycle). For example, processor 118 may coordinate lightdeflector 114 and light source 112 such that when light deflector 114 islocated at a particular instantaneous position, a portion of a lightbeam is deflected by the light deflector from light source 112 toward anobject in the LIDAR FOV, and reflections of the portion of the lightbeam from the object are deflected by the deflector toward at least onesensor 116. In some embodiments, more than one light source may be used.For example, a plurality of light sources may be aimed at deflector 114,and processor 118 may control deflector 114 such that when deflector 114is located at a particular instantaneous position, light from theplurality of light sources is projected towards a plurality ofindependent regions in the LIDAR FOV.

An available optical budget may be apportioned to one or more portionsof the LIDAR FOV in any suitable manner. In some embodiments, e.g.,where processor 118 determines that the vehicle is travelling on ahighway, processor 118 may allocate the available optical budget toportions of the LIDAR FOV such that central region 4720 receives morelight flux than is provided to right peripheral region 4724 or leftperipheral region 4722. For example, processor 118 may be configured tocoordinate the control of light source 112 with the control of deflector114 such that during a first scanning cycle, light having a first lightflux is directed to the central region 4720. After determining that thevehicle is travelling on a highway, processor 118 may change lightapportionment such that during a second scanning cycle, light having asecond light flux is directed to the central region 4720, and whereinthe second light flux is greater than the first light flux. As a resultof increased light flux in the central region of the LIDAR FOV relativeto peripheral regions of the LIDAR FOV, a detection range in the centralregion may be greater than a detection range in the peripheral regions.In some cases, processor 118 may control light source 112 such that adetection distance in the central region is at least two times greaterthan the detection distances in the right peripheral region and in theleft peripheral region.

Of course, the LIDAR FOV may be segmented into more or fewer than threeregions. Additionally, any of the segments may be further divided into aplurality of sub-regions. And, processor 118 may be configured such thatduring a scan of the field of view, more light is directed to one of theplurality of sub-regions than to another of the plurality ofsub-regions.

Just as light apportionment may change based on a determination that thehost vehicle is travelling on a highway, processor 118 may reallocate anoptical budget based on a determination that the vehicle has exited thehighway or that an environment of the vehicle has otherwise changed fromthe highway environment. For example, in cases where the vehicletransitions from road types, such as highway to urban, processor 118 mayreallocate the available optical budget. For example, upon changing froma highway environment to an urban environment, processor 118 may reducelight flux projected toward the central region 4720 (as compared to oneor more previous scanning cycles) and may increase light applied to oneor more of the peripheral regions (as compared to one or more previousscans).

Such apportionment of an available optical budget to selected regions ofa LIDAR FOV may be referred to as defining a spatial light scanningpattern. In some embodiments, processor 118 may determine a spatiallight scanning pattern associated with a plurality of scanning cyclesupon obtaining data indicative of a type of road on which the vehicle istraveling. As noted above, the type of road may include at least one of:an urban road, a highway road, an undivided road, a road with a singlelane per direction, a road with a plurality of lanes per direction, or aroad with a public transportation lane. And upon obtaining dataindicative of a change of the type of road on which the vehicle istraveling (e.g., from a highway to an undivided road), less light may bedirected to the central region and more light may be directed to theright peripheral region and the left peripheral region compared to thelight projected in a prior scanning cycle.

Processor 118 may apportion the available optical budget not based notonly upon a determination of a type of road on which the host vehicletravels, but also may apportion the available optical budget based ondetected driving events. For example, FIG. 48A represents a scenario asdescribed above. Processor 118 may determine that the vehicle hasentered a highway, and as a result of this event, processor 118 mayallocate the available optical budget such that more light flux (e.g.,higher light power levels) may be supplied to the central region ascompared to either the right or left peripheral regions.

In FIG. 48B, processor may determine that the vehicle has entered anarea where the road may be closes bounded by buildings on either side.Such a scenario may occur, for example, in an urban environment. Basedon the detection of the driving event of entering an urban road setting,processor 118 may cause more light flux to be supplied to the left andright peripheral regions than is supplied to the central region. Such anallocation of the optical budget may be suitable for urban environmentswhere vehicle speed is typically lower than highway speeds (meaning thata detection range forward of the vehicle need not be as great in anurban environment and what might be preferred in an highwayenvironment). Further, in an urban environment, there may be more riskof encounters with pedestrians, which may reside in regions to eitherside of the vehicle (e.g., on sidewalks adjacent to the illustratedbuildings). Thus, in an urban environment, enhancing detection range andor resolution capabilities in the peripheral regions of a LIDAR FOVrelative to a central region may be beneficial.

FIG. 48C provides another example of a detected driving event that maytrigger a change in allocation of the available optical budget tocertain regions of the LIDAR FOV. For example, as shown, another vehicle102 may be detected in a lane adjacent to the host vehicle with bothvehicle 102 and the host vehicle being determined as moving in the samedirection. In such a scenario, processor 118 may determine that an areaforward and to the right of the host vehicle constitutes a region ofinterest, as that is the region in which vehicle 102 is located. To aidin detection and/or tracking of vehicle 102, processor 118 may allocatedthe available optical budget such that the right peripheral regionreceives a highest level of light flux, the central region receives thenext highest level of light flux, and the left peripheral regionreceives the lowest level of light flux.

FIG. 48D provides yet another example of a detected driving event thatmay trigger a change in allocation of the available optical budget tocertain regions of the LIDAR FOV. For example, as shown, another vehicle102 may be detected in a lane adjacent to the host vehicle with vehicle102 and the host vehicle being determined as moving in oppositedirections. In such a scenario, processor 118 may determine that an areaforward and to the left of the host vehicle constitutes a region ofinterest, as that is the region in which vehicle 102 is located (andwhere oncoming traffic is expected to be found). To aid in detectionand/or tracking of vehicle 102, processor 118 may allocated theavailable optical budget such that the left peripheral region receives ahighest level of light flux, the central region receives the nexthighest level of light flux, and the right peripheral region receivesthe lowest level of light flux. Further, as shown in FIG. 48D, aparticular sub-region of the left peripheral region may be defined, andprocessor 118 may cause the highest level of light flux (even within theleft peripheral region) to be supplied to the particular sub-region. Insome cases, the defined sub-region of the left peripheral region mayoverlap with a location of the detected vehicle 102.

Processor 118 may allocate or re-allocate an available optical budgetbased on other detected driving events as well. For example, in someembodiments the detected driving event justifying allocation orre-allocation of the optical budget may include at least one of atraffic-related event, a road-related event, an approach to a predefinedestablishment, and a weather-related event. Based on detection or anindication of any of these types of events, processor 118 may alter thespatial light scanning pattern from one scanning cycle to another. Forexample, processor 118 may alter the spatial light scanning pattern suchthat more light is directed to at least a portion of the rightperipheral region than was directed to the at least a portion of theright peripheral region in a prior scanning cycle, such that more lightis directed to at least a portion of the left peripheral region than wasdirected to the at least a portion of the left peripheral region in aprior scanning cycle, such that more light is directed to at least aportion of the central region than was directed to the at least aportion of the central region in a prior scanning cycle, etc.

FIG. 49 provides a flow chart representation of a method 4900 foroperating a LIDAR system consistent with presently disclosedembodiments. The method may include controlling at least one lightsource in a manner enabling light flux of light from at least one lightsource to vary over a scanning cycle of a field of view (step 4910). Themethod may also include controlling at least one deflector to deflectlight from the at least one light source in order to scan the field ofview, wherein the field of view is dividable into a central regiongenerally corresponding to the highway on which the vehicle istraveling, a right peripheral region generally corresponding to an arearight of the highway, and a left peripheral region generallycorresponding to an area left of the highway (step 4920). At step 4930,processor 118 may obtain input that the vehicle is in a modecorresponding to highway travel, and in response, as step 4940,processor 118 may coordinates the control of the at least one lightsource with the control of the at least one light deflector such thatduring scanning of the field of view that encompasses the centralregion, the right peripheral region, and the left peripheral region,more light is directed to the central region than to the rightperipheral region and to the left peripheral region.

Varying Lidar Illumination Responsive to Ambient Light Levels

A LIDAR system may be used in many different environments havingdiffering levels of ambient light. In addition, levels of ambient lightmay drastically differ within a single scene at any one time. Forexample, parts of the scene may be shaded, other may be illuminated bysunlight or other light sources, and yet other parts of the field mayinclude ambient light source such as lamps, headlights, open fire, etc.Such ambient light may cause noise which, in turn, may lower the qualityof service (QoS) of the LIDAR system. In situations where LIDAR system100 operates in the presence of high ambient light (e.g., brightsunlight or artificial light sources), LIDAR system 100 may experiencesignificant noise from the ambient noise. On the other hand, if theLIDAR system 100 operates in environments with less ambient light, thenoise may be lesser.

As described, systems and methods consistent with the presentlydisclosed embodiments may collect light reflection data and allocatelight flux on a pixel-by-pixel basis, on a beam-spot-by-beam-spot basis,or on a portion by portion basis relative to a LIDAR FOV (it is notedthat in the description below, implementations which are discussed withrespect to any one of these aforementioned bases may also beimplemented, mutatis mutandis, with respect to the other two bases). Insome instances, the amount of light flux allocated to a particularportion of the LIDAR FOV may depend on an amount of ambient lightdetected in the particular region of the FOV. Especially, in someinstances, the amount of light flux allocated to a particular portion ofthe LIDAR FOV (e.g. to a specific pixel) in a given scanning cycle maydepend on an amount of ambient light detected in that particular regionof the FOV in the same scanning cycle. In some instances, the amount oflight flux allocated to a particular portion of the LIDAR FOV (e.g. to aspecific pixel) in a given instantaneous position of the at least onelight deflector 114 may depend on an amount of ambient light detected inthat particular portion of the FOV while the at least one lightdeflector 114 remained in that particular instantaneous position (e.g.,without any emission to any other portion of the FOV intermittentbetween the detection of the ambient light to the emission of theallocated light flux). For example, where an amount of ambient light ina particular region of the FOV is determined to be low, lower amounts oflight flux may be supplied to that particular region. On the other hand,as more ambient light is detected within a particular region of the FOV,the amount of light flux provided to that region may be increased. Byvarying light allocation to regions of the LIDAR FOV based on levels ofdetected ambient light, effects of noise on the operation of LIDARsystem 100 may be reduced or eliminated.

In some embodiments, the field of view (e.g., FOV 120, as shown in FIG.50) may include a plurality of portions, each corresponding to adifferent instantaneous position of deflector 114. Each of the portionsmay have any suitable size and/or occupy any suitable portion of FOV120.

The at least one processor 118 may receive, on a pixel by pixel basis,signals from at least one sensor 116, as shown in FIG. 50). For example,the at least one sensor may detect light collected from a specificportion of the FOV on a pixel-by-pixel basis (e.g., pixels A1, B1, C1,A2, etc. of FOV 120 as shown in FIG. 51) and generates signalscorresponding to light collected for each pixel. The signals may beindicative of multiple sources of light collected from the FOV. Forexamples, one component of the light collected and provided to sensor116 may include ambient light. Another component of the light collectedand provided to sensor 116 may include light from the at least one lightsource 112 that is projected to the particular portion of the FOV andreflected by one or more objects in the particular portion of the fieldof view. In certain situations (e.g., where an object is distant or hasa low reflectivity), the ambient light collected from a particularportion of the LIDAR FOV may account for a greater proportion of lightprovided to sensor 116 than the reflected light originating from theLIDAR illumination. In other situations (e.g., where an object is closeror has a higher reflectivity), the ambient light collected from aparticular portion of the LIDAR FOV may account for a smaller proportionof the light provided to sensor 116 than the reflected light. Forexample, in a first portion of the LIDAR FOV (represented by theparticular regions of the FOV shown in white in FIG. 51), the ambientlight may account for a greater proportion of the light collected fromFOV 120 than reflected light collected from a second portion of FOV 120(represented by the particular regions of the FOV shown with shading inFIG. 51). It should be noted that the first and second portions of theLIDAR FOV may each include more or fewer particular regions of the LIDARFOV than what is shown in FIG. 51. For example, in some embodiments, thefirst and/or second portions may each correspond to a single particularregion of FOV 120 or may include a plurality of portions (as shown).

Based on the output of sensor 116, processor 118 may be configured todetect ambient light in a particular portion of the LIDAR FOV separatelyfrom detection of projected light reflected from objects. For example,in some embodiments, processor 118 may sample an output of sensor 116 attimes when reflected light is not expected. For example, prior to alight emission from projector 112 toward a particular portion of theFOV, reflected light would not be expected from the particular portionof the FOV, as no light has yet been projected there. Thus, light sensedby the sensor 116/processor 118 may be assumed to correspond to ambientlight. Similarly, after light has been projected to the particularportion, but after a sufficient time has elapsed such that noreflections are expected from the light projection (e.g., at a timegreater than or equal to a time corresponding to the time of flight oflight to and from a maximum expected range of the LIDAR system for aparticular light emission), light gathered from a particular portion ofthe FOV may be attributed to ambient light. In some embodiments,following light emission by light projector 112, sensor 116 may detectreflections of light from the field of view in a first sensing durationfollowing the light emission. And sensor 116 may measure anambient-light level in the field of view in a second sensing durationfollowing the light emission. By monitoring the output of sensor 116 atsuch times, an ambient light level in a particular portion of the FOVmay be determined.

Optionally, processor 118 may be configured to determine an amount ofambient light in a particular portion of the FOV during a time whenlight projected to the particular portion is reflected from one or moreobjects and received by sensor 116. For example, in some cases, theprojected light may be associated with one or more characteristics(e.g., wavelength, modulation pattern, pulse duration, etc.) that may besensed and/or differentiated from background ambient light, for example,based on an output of sensor 116 or one or more other sensors. In somecases, LIDAR system 100 may include a first sensor configured to detectreflections of light from objects in the field of view and a secondsensor configured to measure the ambient light in the field of view. Inother cases, sensor 116 may detect both reflections from objects andambient light. Differentiating ambient light from reflected light inthis manner may enable determination of an amount of ambient lightpresent in a particular portion of the FOV. In some examples, receivedlight which is determined by processor 118 to be a reflections signal oflight emitted by the LIDAR (e.g. based on a matching filter) may besubtracted from the overall receive signal, to provide an estimation ofambient light level.

In some embodiments, processor 118 may be configured to identify a typeof light source or sources associated with the ambient light detected ina particular portion of the LIDAR FOV. For example, after receivingsensed light information associated with a specific portion of the FOV,processor 118 may compare the received information with the pre-storednoise-level data associated with various sources of ambient light. Basedon such a comparison, processor 118 may identify a type of light sourcefrom which the ambient light may have originated. Processor 118 may alsouse other characteristics of the ambient light (e.g., polarization,fluctuations levels) and/or information from multiple pixels (e.g.physical size estimation, distance between light sources) in for theidentification of the type of the light source. It is noted that theidentification of the type of the light source may later be used forobject classification (e.g., headlights may indicate that the object isa car or a semitrailer truck, based on a distance between theheadlights), and vice versa (object features may be used to identify thelight source, e.g. high lights sources in buildings may be identified aslit windows).

In some embodiments, where ambient light levels are sensed in aparticular region of the LIDAR FOV, processor 118 may determine anallocation of light to be projected to that particular portion of theFOV based on the sensed ambient light levels. For example, if the sensedambient light levels are below a predetermined threshold/value,processor 118 may determine that no additional light needs to beprojected to the particular FOV portion. On the other hand, if thesensed ambient light levels are above a predetermined threshold/value,then processor 118 may determine that additional light should beprojected to the particular FOV portion. In such instances, processor118 may cause additional light flux to be supplied to the particularportion of the FOV.

As just one example represented by the diagram of FIG. 51, a firstportion of the FOV includes fifteen particular regions of the FOV, and asecond portion of the FOV includes 25 particular regions. The regions ofthe second portion were all determined to have ambient light levelsbelow a predetermined level. Thus, in these regions, only one pulse oflight (or any other type of light projection affecting an amount oflight flux provided to a particular FOV region) has been allocated tothe regions of the second portion of the FOV. On the other hand, each ofthe regions of the FOV in the first portion were determined to haveambient light levels above the predetermined ambient light levelthreshold/value. As a result, processor 118 has allocated three lightpulses to be projected toward each of the regions included in the secondportion of the FOV. Of course, the concept of light pulses provided toregions of the FOV is exemplary only. Any other type of light projectiontechniques may be used in order to increase light flux in the regions ofthe first portion of the FOV relative to the amounts of light providedto the regions of the second portion of the FOV.

It is also noted that other considerations may be used, in addition tothe detection of ambient light levels, for determining the amount offlux which will be provided to different portions of the FOV (e.g., todifferent pixels) during each scanning cycle. For example, processor 118may decide not to allocate additional light to a portion in which lightsource is detected, if that portion is included in a predefined regionof no interest. Processor 118 may combine the information of thedetermined ambient light levels in a portion of the FOV with informationindicative of other noise levels of that portion, or with any other typeof information (from the same scanning cycle or not) which is disclosedin the present disclosure as usable for determining flux levels.

An amount of light that processor 118 allocates to a particular regionof the FOV may also depend on a determined type of light sourceassociated with ambient light detected in the particular region. Forexample, more light may be allocated to the particular region if theambient light is determined to have originated from the sun rather thanfrom an electric lamp, for example, Of course, the reverse may also betrue.

To scan the FOV (e.g. FOV 120 of FIG. 50), the at least one processor118 may coordinate the at least one light deflector and the at least onelight source such that, when the at least one light deflector is locatedat a particular instantaneous position, a light beam is deflected by theat least one light deflector from the at least one light source towardsthe field of view and reflections from an object in the field of vieware deflected by the at least one light deflector toward at least onesensor. Accordingly, the at least one light deflector may direct a lightbeam toward the field of view and also receive a reflection from thefield of view. For example, FIGS. 1A, 2B, and 2C depict examples inwhich a deflector both directs a light beam towards the field of viewand also receives a reflection from the field of view. In certainaspects, the reflection may be caused by the light beam directed towardthe field of view. In other embodiments, a light beam from the at leastone light source may be directed towards the field of view by at leastone light deflector separate from at least one other light deflectorthat receives a reflection from the field of view. For example, FIG. 2Adepicts an example in which one deflector directs a light beam towardsthe field of view and a separate deflector receives a reflection fromthe field of view.

In some embodiments, a sensitivity level associated with sensor 116 maybe controlled based on detected ambient light and/or whether lightsources are detected, for example, in a particular region of the LIDARFOV (for example, during the same scanning cycle, but not necessarilyso). For example, processor 118 may be configured to identify, based onthe received information from sensor 116, an existence of a light sourcein a particular portion of the LIDAR FOV. In response to identificationof such a light source, processor 118 may alter a sensor sensitivityrelative to light reflections from the particular portion of the LIDARFOV.

As explained above, as more ambient light is detected within aparticular region of the FOV, the amount of light flux provided to thatregion may be increased, in order to reduce or eliminate the effects ofnoise. The at least one processor 118 may cause the at least one lightsource (e.g., light source 112 of FIG. 50) to project a higher lightflux toward a portion of a field of view (e.g., field of view 120 ofFIG. 50). The higher light-flux projected toward a particular portion ofthe FOV may improve a signal to noise ratio (or otherwise improve thedetection probability in this portion of the FOV, e.g. as discussedabove), and therefore may increase the QoS for an object located in theportion of the field of view.

The at least one processor 118 may also obtain an identification of atleast one distinct region of interest in a portion of the field of viewand may increase light flux in the region of interest. For example,light flux may be increased by increasing the number of light pulse persolid angle, increasing irradiance versus FOV portion, emittingadditional light pulses, increasing power per pixel, emitting additionalphotons per unit time, increasing the aggregated energy over a certainperiod of time, emitting additional photons per data point in agenerated point cloud model, increasing aggregated energy per data pointin a generated point cloud model, altering the wavelength, increasingthe amplitude and/or frequency of the light pulses, or any othercharacteristic of increasing light flux. In some cases, the region ofinterest may be a particular region of the LIDAR FOV determined to havea level of ambient light meeting at least one predeterminedcharacteristic (e.g., ambient light level, type of light source, nightor daytime operation (ambient light sources indicative of headlights atnight), etc.).

A particular region of interest in a portion of a field of view may alsobe identified based on information received from at least one of a GPSunit, a vehicle navigation system, a radar, a LIDAR, a camera, etc.Based on the identification, the at least one processor 118 may causethe at least one light source (e.g., light source 112 of FIG. 50) toproject a higher light flux toward a portion of a field of view thanwhat is projected in other portions of the field of view. For example, asignal from a camera may indicate that the LIDAR system 100 is in abright environment (e.g., under a light source or under the sun). Tocompensate for high levels of noise associated with such light sources,the at least one processor 118 may cause light source 112 to project ahigher light flux toward a portion of the LIDAR field of view.

To project more light toward a portion in a FOV, the at least oneprocessor 118 may cause the at least one light source 112 to projectmore light-pulses. For example, the at least one processor 118 may varythe timing of pulses from the at least one light source. To increase thenumber of the light-pulses in a portion, the at least one processor mayshorten the timing of the pulses. By way of further example, processor118 may alternatively or concurrently vary power level, of pulses fromthe at least one light source. In a yet further example, processor 118may alternatively or concurrently vary the amplitude and/or frequency ofpulses from the at least one light source. For example, in FIG. 51, thesystem may determine to project one light-pulse per pixel as default.Because the first portion of FOV 120 may contain a higher ambient lightand the received signal may be greater than the predetermined threshold,three light pluses per pixel, instead of one per pixel, may be projectedin the first portion of FOV, as described above. In some embodiments,the intensity of light projected to the regions of the first portion ofthe FOV in FIG. 51 may be greater than an intensity of light provided tothe second portion of the FOV in FIG. 51.

Moreover, processor 118 may be configured to alter a light sourceparameter associated with light projector 112 such that in a singlescanning cycle, more light-pulses per solid angle are projected towardthe first portion of the FOV than a number of light-pulses per solidangle projected toward the second portion of the FOV in FIG. 51. In somecases, rather than even providing a default level of light to certainregions of the LIDAR FOV, processor 118 may be configured to alter alight source parameter associated with light projector 112 such thatduring at least one single scanning cycle for the LIDAR FOV, no light isprojected towards the second portion of the field of view shown in FIG.51. In another example, processor 118 may also be configured to alterthe light source parameter such that the light projected toward thefirst portion is at a different wavelength than the light projectedtoward the second portion.

FIG. 52 illustrates an example method 5200 for detecting objects using aLIDAR system. At step 5201, as explained above, processor 118 maycontrol at least one light source (e.g., light source 112 of FIG. 1A,laser diode 202 of light source 112 of FIG. 2A, and/or plurality oflight sources 102 of FIG. 2B) in a manner enabling light flux to varyover a scan of a field of view (e.g., field of view 120 of FIGS. 1A and2A). At step 5202, at least one processor 118 controls at least onelight deflector (e.g., light deflector 114 of FIG. 1A, deflector 114Aand/or deflector 114B of FIG. 2A, and/or one-way deflector 214 of FIG.2B) in order to scan the field of view. For example, processor 118 maycause mechanical movement of the at least one light deflector to scanthe field of view. Alternatively or concurrently, processor 118 mayinduce a piezoelectric or thermos-electrical change in the at least onedeflector to scan the field of view. In some embodiments, a singlescanning cycle of the field of view may include moving the at least onedeflector such that, during the scanning cycle, the at least one lightdeflector is instantaneously located in a plurality of positions. Forexample, the at least one light deflector may be moved from one of theplurality of positions to another (optionally with additional positionsand/or repetitions) during the scanning cycle rather than being moved ina continuous sweep.

At step 5203, the at least one processor 118 receives, on a pixel bypixel basis, signals from at least one sensor (e.g., sensing unit 106 ofFIG. 51). For example, the signals may be indicative of at least one ofambient light and light from the at least one light source reflected byan object in the field of view. At step 5204, the at least one processor118 may identify a type of light source at a portion of a field of view,that causes the ambient noise from the received information anddetermine a level of light-flux to allocate the at least one lightsource (e.g., light source 112 of FIG. 1A, laser diode 202 of lightsource 112 of FIG. 2A, and/or plurality of light sources 102 of FIG.2B). At step 5205, as explained above, the at least one processor 118may cause the at least one light source (e.g., light source 112 of FIG.1A, laser diode 202 of light source 112 of FIG. 2A, and/or plurality oflight sources 102 of FIG. 2B) to project a higher light flux toward theportion of the field of view (e.g., field of view 120 of FIGS. 1A and2A). For example, the at least one processor 118 may cause the at leastone light source to project a higher light flux toward the portion ofthe field of view before moving to another portion of the field of view(e.g., while the at least one deflector is still in the sameinstantaneous position).

Temperature Based Control in Lidar

In LIDAR systems it may be important to regulate the temperature of thesystem components to prevent damage to the components themselves and forsafety reasons. Additionally, some components of LIDAR systems mayprovide suboptimal performance when exceeding a temperature range, andit may therefore me important to modify the operation of the LIDARsystem to optimize the performance which can be provided in suchsuboptimal conditions. In some embodiments, a LIDAR system may be usedin a vehicle. A LIDAR system 100 may include one or more light sources112 for projecting light toward a FOV 120 for illuminating one or moreobjects in the FOV 120 that are in the environment of the vehicle. TheLIDAR system 100 may contain one or more processors 118 to vary thelight flux over scans of one or more portions of the FOV 120 bycontrolling the light source 112. During scanning of the FOV 120, heatmay be radiated from one or more of the LIDAR system components. Systemcomponents may include one or more light sources, deflectors, sensors,processors, and/or other LIDAR system components. Heat may also radiatefrom a vehicle in which LIDAR system 100 is installed (especially if theLIDAR system is installed in locations which are hot and/or difficult toventilate, such as under the hood of the vehicle). Heat may also resultfrom weather or other ambient conditions (e.g., driving inside awarehouse). It is also noted that LIDAR system 100 may also be sensitiveto low temperature, which may also result from similar causes.

The processor 118 may receive information, via one or more temperaturesensors, indicating the temperature of one or more components exceeds athreshold temperature. The threshold temperature may be determineddynamically by a processor or may be a static, preset value. Thethreshold temperature may be the temperature at which or above which thecomponent or system is at risk of overheating. In some embodiments, thethreshold temperature may be a percentage of a temperature at which thesystem or a system component is at risk of overeating. For example, thethreshold temperature may be 80% of a temperature at which the system ora system component is at risk of overeating. If the system or acomponent overheats, it could damage the LIDAR system, create a firehazard, and/or cause system functions. If the detected temperature ofone or more system components meets and/or exceeds the threshold, theprocessor 118 may modify an illumination ratio between two portions ofthe FOV 120 so that less light is delivered to the FOV 120 during one ormore subsequent scanning cycles.

As noted above, the temperature threshold may be determined dynamically,and it can be modified based on the state of various components of LIDARsystem 100, of the vehicle in which it is installed, and on otherparameters. It is also noted that the temperature threshold may pertainto the measured temperature, but may also pertain to othertemperature-based parameters (e.g. change of temperature over time,plurality of temperatures measured in different locations, etc.). Inimplementations in which processor 118 implements such complex and/ortime-dependent temperature thresholds, processor 118 may be consideredto implemented a temperature decision rule. Processor 118 may beconfigured to manage high temperatures in the LIDAR system bydetermining when the temperature threshold is exceeded so thatexceedingly high temperatures and/or temperature rise rates aremeasured. Processor 118 may be configured to manage low temperatures inthe LIDAR system by determining when the temperature threshold isexceeded so that exceedingly low temperature and/or too fast temperaturefall rates are measured.

FIG. 53 is a diagrammatic illustration of a LIDAR system consistent withembodiments of the present disclosure. For example, as shown, a LIDARsystem 5300 may contain a light source 5310, sensor assembly 5340, and atemperature sensing unit 5380. In some embodiments, the LIDAR system5300 may contain all or some of the components of LIDAR system 100 and atemperature sensing unit 5380. In some embodiments, LIDAR system 100 maycontain a temperature sensing unit 5380. Temperature sensing unit 5380may be configured to detect the temperature of individual systemcomponents and/or the overall temperature of the LIDAR system 5300.

In some embodiments, LIDAR system 5300 may contain a control system 5300including a sensor interface 5350, a light-source controller 5360, and atemperature processor 5370. The temperature processor 5370 may receivetemperature information from an optional temperature detector 5380 (orfrom other sources, such as external temperature sensor, from the host,etc.) and process the received information to determine if thetemperature of one or more system components or of the LIDAR system 5300exceeds a threshold temperature. If the threshold temperature isexceeded (e.g., during a particular scanning cycle), the temperatureprocessor 5370 may communicate with light-source controller 5360 tomodify the illumination ratio between two portions of the FOV so lesslight is delivered to the FOV during a subsequent scanning cycle,thereby decreasing the temperature of the one or more system componentsand/or the LIDAR system 5300. In some embodiments, the LIDAR system 5300may include cooling components to cool system components havingtemperatures that meet or exceed the threshold.

In some embodiments, the processor 118 may be configured to control oneor more light deflectors 114 such that during a scanning cycle of theFOV, one or more light deflectors 114 are located in one or moredifferent instantaneous positions. The processor 118 may also coordinateone or more light deflectors 114 and one or more light sources 112 suchthat when a light deflector 114 is located at a particular instantaneousposition, a portion of a light beam is deflected by the deflector 114from the light source 112 towards an object in the FOV 120. Reflectionsof the portion of the light beam from the object may be deflected by theone or more deflectors 114 toward one or more sensors 116. In someembodiments, one or more light sources 112 may be aimed at one or morelight deflectors 114. Processor 118 may control the one or more lightdeflectors 114 such that when a light deflector 114 is located at aparticular instantaneous position, light from one or more light sources112 may be projected towards several independent regions in the FOV 120.

In some embodiments, the processor 118 may determine, based on thetemperature information, a spatial light distribution in a singlescanning cycle of the FOV and modify the illumination ratio so morelight is projected toward a first portion of the FOV than a secondportion of the FOV. In some embodiments, the processor 118 may, based onthe temperature information, coordinate control of one or more lightsources 112 and one or more light deflectors 114 such that during one ormore subsequent scanning cycles, the same amount of light is projectedtowards a portion of the FOV as was projected in the prior scanningcycle. In some embodiments, the processor 118 may, based on thetemperature information, coordinate control of one or more light sources112 and one or more light deflectors 114 to project more light-pulsestoward the first portion of the FOV than toward the second portion ofthe FOV. In some embodiments, the processor 118 may, based on thetemperature information, coordinate control of one or more light sources112 and one or more light deflectors 114 in one or more scanning cyclesto dynamically adjust the rate of scanning cycles for illuminating thefirst portion of the FOV and the rate of scanning cycles forilluminating the second portion of the FOV. Adjusting the scanning cyclerate may decrease the temperature of one or more system components. Insome embodiments, the processor 118 may restore the settings of theLIDAR system 100 once the temperature of the system or one or morecomponents returns to a value lower than the threshold temperature.

In some embodiments, processor 118 may identify a region of interest ina portion of the FOV and modify, based on the temperature information,the illumination ratio between the portion of the FOV and anotherportion of the FOV such that during one or more subsequent scanningcycles, more light is directed toward the portion of the FOV containinga region of interest. In some embodiments, processor 118 may identifyregions of non-interest in a portion of the FOV. Based on a region ofinterest determination and on the temperature information, more lightflux may be allocated to regions of interest than to regions of theLIDAR FOV of less interest or not in a determined region of interest. Asa result, illumination of a region of interest (e.g., with a differentscanning rate, power level, light intensity, light flux, pulse duration,number of pulses, etc.) may increase localized heating in one or morecomponents of LIDAR system 100 in an optical path of the projected light(e.g., deflector 114, etc.). Thus, temperature management through lightallocation techniques described herein may become more important forcertain portions of system components when regions of interest are beingilluminated.

In some embodiments, the processor 118 may receive information that thetemperature associated with one or more components of the LIDAR system100 (or one or more portions of those components) exceeds a thresholdtemperature. The processor 118 may receive temperature information via awired or wireless connection a temperature sensing component, such astemperature sensor 5380. In some embodiments, the processor 118 mayreceive information from the vehicle controller that the temperature ofone or more system components exceeds a threshold, which may involve oneor more additional processors.

In some embodiments, temperature information received by processor 118may include information about the temperature of the environmentexternal to the vehicle, information about the vehicle's engine heat,information about a temperature of one or more light sources 112, and/orinformation about a temperature of the one or more processors, includingprocessor 118.

In some embodiments, processor 118 may determine a value for thethreshold temperature based on information about a temperature of anenvironment surrounding the vehicle. For example, on a hot day thethreshold temperature may be lowered to account for the external heatfrom the sun or from the air surrounding the LIDAR system 100.

In some embodiments, processor 118 may reduce a resolution in a part ofthe FOV if the temperature of one or more system components exceeds atemperature threshold. The resolution may be reduced in areas of the FOVwith less illumination, but the detection distance may be the same asthe detection distance achieve with the original resolution. In someembodiments, a farther detection distance is achieved with the lowerresolution than with the original resolution.

FIG. 54 is an exemplary flow chart of an exemplary process 5400 fordetecting the temperature of one or more components of a LIDAR system100. At step 5402 the LIDAR system 100 begins a scanning cycle at aninitial scanning rate. In some embodiments, step 5402 may not occurduring each scanning cycle, but rather at a predetermined interval. Inother embodiments, step 5402 may occur outside a scanning cycle, forexample, when the LIDAR system is turned on or initiated. At step 5404,processor 118 may receive information from one or more temperaturesensors 5380 indicating the temperatures of one or more systemcomponents. Processor 118 may determine whether or not the temperatureof a system component meets or exceeds a threshold temperature at step5404. If the threshold temperature is not met, the component orcomponents are not at risk of overheating (or, alternatively, freezing)and the LIDAR system 100 may execute the subsequent scanning cycle withno measures to alter the component's temperature. If the thresholdtemperature is met or exceeded, processor 118 may act to restrict (e.g.,decrease) the temperature of component by adjusting the LIDAR system 100to emit less overall light in the FOV (step 5408) thereby decreasing thetemperature of the component. In some embodiments, the processor 118 mayact to prevent the temperature of the component from reaching thethreshold temperature. In some embodiments, the processor 118 may adjustthe illumination ratio between portions of the FOV during the followingscanning cycle. Based on which component is at risk of overheating, theprocessor 118 may employ different heat reduction techniques. In someembodiments, the processor 118 may decrease the scanning rate in thefollowing scanning cycle. In some embodiments, processor 118 may reducethe resolution in the following scanning cycle. In other embodiments,the processor 118 may control a cooling component to cool the componentoverheating or at risk of overheating. In other embodiments, theprocessor 118 may control a heating component to heat a componentfreezing or at risk of freezing.

FIG. 55 is an exemplary flow chart of an exemplary process 5500 fordetermining a threshold temperature and detecting the temperature of oneor more components of a LIDAR system 100 in a vehicle. At 5502 the LIDARsystem 100 begins the process of determining the component temperatures.A processor 118 may receive temperature information from one or moresensors, such as temperature sensor 5380, indicating the temperatures ofone or more system components, the vehicle engine, and/or theenvironment around the vehicle. At step 5504 the processor 118 mayreceive information from one or of the above described temperaturesensors. At step 5506, the processor 118 may use an algorithm or othermethod of calculation to determine an appropriate threshold temperaturefor a system component based on the vehicle engine temperature, thetemperature inside the vehicle, and/or the temperature of theenvironment around the vehicle. The calculated threshold temperature mayalso account for a temperature at which a component begins to performsub-optimally. The processor 118 may determine whether the componenttemperatures is greater than or equal to the calculated thresholdtemperature at step 5508. If the temperature does not meet thethreshold, the processor 118 may take no action until the temperature isnext evaluated. The process 5500 may occur at a predetermined timeinterval, independent from the LIDAR system 100 scanning cycles. Thecalculated threshold temperature may be calculated during each scanningcycle or may be calculated repeatedly at another interval. For example,the threshold may be calculated every five minutes, 30 minutes, twohours, etc.

If the component temperature is greater than or equal to the thresholdtemperature, processor 118 may modify the scene projection scheme toemit less light in the FOV at step 5510. As described above, theprocessor 118 may reduce the component temperature in a number of ways.The process 5500 may then restart at the next predetermined interval. Insome embodiments, the modifications made in step 5510 may be reversed,thereby restoring performance of the component when the component'stemperature is below the threshold temperature.

MEMS Mirror and Actuation Techniques

FIG. 56 illustrates an example embodiment of a scanning device (e.g.,deflector 114 hereinafter “scanning device 8202”) and a processingdevice (e.g., processor 118 hereinafter controller 8204). Consistentwith the present disclosure, controller 8204 may be local and includedwithin scanning device 8202. Controller 8204 may include at least onehardware component, one or more integrated circuits, one or more FPGAs,one or more ASICs, one or more hardware accelerators, and the like. Acentral processor unit (CPU) and an actuation driver are some examplesof a controller 8204.

As shown in FIG. 56, a mirror configuration may include mirror 8206which can be moved in two or more axes (θ, φ). Mirror 8206 may beassociated with an electrically controllable electromechanical driversuch as actuation driver 8208. Actuation driver 8208 may cause movementor power to be relayed to an actuator/cantilever/bender such as actuator8210. Actuator 8210 may be part of a support frame such as frame 8211.Additional actuators, such as actuators 8212, 8214 and 8216, may each becontrolled/driven by additional actuation drivers as shown, and may eachhave a support frame 8213, 8215 and 8217 (appropriately). It isunderstood that frames 8211, 8213, 8215 and/or 8217 may comprise asingle frame supporting all of the actuators or may be a plurality ofinterconnected frames. Furthermore, the frames may be electricallyseparated by isolation elements or sections. Optionally, a flexibleinterconnect element or connector (interconnect), such as spring 8218,may be utilized to adjoin actuator 8210 to mirror 8206, to relay poweror movement from actuation driver 8208 to spring 8218.

Actuator 8210 may include two or more electrical contacts such ascontacts 8210A, 8210B, 8210C and 8210D. Optionally, one or more contacts8210A, 8210B, 8210C and/or 8210D may be situated on frame 8211 oractuator 8210 provided that they are electronically connected. Accordingto some embodiments, actuator 8210 may be a semiconductor which may bedoped so that sections actuator 8210 (except the piezoelectrical layerthat is insulative) is generally conductive between contacts 8210A-210Dand isolative in isolation 8220 and 8222 to electronically isolateactuator 8210 from actuators 8212 and 8216 (respectively). Optionally,instead of doping the actuator, actuator 8210 may include a conductiveelement which may be adhered or otherwise mechanically or chemicallyconnected to actuator 8210, in which case isolation elements may beinherent in the areas of actuator 8210 that do not have a conductiveelement adhered to them. Actuator 8210 may include a piezoelectric layerso that current flowing through actuator 8210 may cause a reaction inthe piezoelectric section which may cause actuator 8210 to controllablybend.

According to some embodiments. Controller 8204 may output/relay tomirror driver 8224 a desired angular position described by θ, φparameters. Mirror driver 8224 may be configured to control movement ofmirror 8206 and may cause actuation driver 8224 to push a certainvoltage amplitude to contacts 8210C and 8210D in order to attempt toachieve specific requested values for θ, φ deflection values of mirror8206 based on bending of actuators 8210, 8212, 8214 and 8216. Inaddition, position feedback control circuitry may be configured tosupply an electrical source (such as voltage or current) to a contact,such as contact 8210A or 8210B, and the other contact (such as 8210B or8210A, respectively) may be connected to a sensor within positionfeedback 8226, which may be utilized to measure one or more electricalparameters of actuator 8210 to determine a bending of actuator 8210 andappropriately an actual deflection of mirror 8206. As shown, additionalpositional feedback similar to position feedback 8226 and an additionalactuation driver similar to actuation driver 8208 may be replicated foreach of actuators 8212-216 and mirror driver 8224 and controller 8204may control those elements as well so that a mirror deflection iscontrolled for all directions.

The actuation drivers including actuation driver 8208 may push forward asignal that causes an electromechanical reaction in actuators 8210-216which each, in turn is sampled for feedback. The feedback on theactuators' (8210-8216) positions serves as a signal to mirror driver8224, enabling it to converge efficiently towards the desired positionθ, φ set by the controller 8204, correcting a requested value based on adetected actual deflection. According to some embodiments, a scanningdevice or LIDAR may utilize piezoelectric actuator micro electromechanical (MEMS) mirror devices for deflecting a laser beam scanning afield of view. Mirror 8206 deflection is a result of voltage potentialapplied to the piezoelectric element that is built up on actuator 8210.Mirror 8206 deflection is translated into an angular scanning patternthat may not behave in a linear fashion, for a certain voltage levelactuator 8210 does not translate to a constant displacement value. Ascanning LIDAR system (e.g., LIDAR system 100) where the field of viewdimensions are deterministic and repeatable across different devices isoptimally realized using a closed loop method that provides an angulardeflection feedback from position feedback and sensor 8226 to mirrordriver 8224 and/or controller 8204.

In some embodiments, position feedback and sensor 8226 may also beutilized as a reliability feedback module. According to someembodiments, a plurality of elements may include semiconductors orconducting elements, or a layer and accordingly, actuators 8201-8216could at least partially include a semiconducting element, springs 8218,8226, 8228 and 8230 may each include a semiconductor, and so may mirror8206. Electrical Power (current and/or voltage) may be supplied at afirst actuator contact via position feedback 8226, and position feedback8226 may sense an appropriate signal at actuator 8212, 8214 and/or 8216via contacts 8214A or 8214B and/or 8216A or 8216B. Some of the followingfigures illustrate MEMS mirrors, actuators and interconnects. The numberof interconnects, the shape of the interconnects, the number ofactuators, the shape of the actuators, the shape of the MEMS mirror, andthe spatial relationships between any of the MEMS mirror, actuators andinterconnects may differ from those illustrated in the followingfigures.

Interconnects

FIG. 57 illustrates four L-shaped interconnects 9021, 9022, 9023 and9024 that are connected between circular MEMS mirror 9002 and fouractuators 9011, 9012, 9013 and 9014. Each L-shaped interconnect (forexample 9021) includes a first segment 90212 and a second segment 90211.The first and second segments are mechanically connected to each other.In FIG. 57 the first and second segments are normal to each other. InFIG. 57 the second segment of each L-shaped interconnect is connected toa circumference of an actuator and the first segment of each L-shapedinterconnect is connected to the circumference of the MEMS mirror. Thesecond segment is normal to the circumference of first actuator. Thefirst segment is normal to the circumference of the MEMS mirror and/ormay be directed towards a center of the MEMS mirror when the MEMS mirroris at an idle position. The MEMS mirror is at an idle position when allof the actuators that are coupled to the MEMS mirror are not subjectedto a bending electrical field.

In one embodiment, using L-shaped interconnects may provide superiordurability and stress relief. Using the L-shaped interconnectsfacilitates seamless movement about two axes of rotation (see dashedlines denoted AOR near interconnect 9024) that are normal to each other.Thereby, the bending and unbending of an actuator does not impose anundue stress on the L-shaped interconnect. Furthermore, the L-shapedinterconnects are relatively compact and may have a small volume, whichreduces the mechanical load imposed on the actuators, and may assist inincreasing the scanning amplitude of the MEMS mirror. It should be notedthat the different segments of the interconnect may be oriented inrelation to each other (and/or in relation to the MEMS mirror and/or inrelation to the actuator) by angles that differ from ninety degrees.These angles may be substantially equal to ninety degrees (substantiallymay mean a deviation that does not exceed 5, 10, 15 or 20 percent andthe like). It should further be noted that the L-shaped interconnectsmay be replaced by interconnects that include a single segment or morethan a pair of segments. An interconnect that has more than a singlesegment may include segments that are equal to each other and/orsegments that differ from each other. Segments may differ by shape,size, cross section, or any other parameter. An interconnect may alsoinclude linear segments and/or nonlinear segments. An interconnect maybe connected to the MEMS mirror and/or to the actuator in any manner.

FIG. 58 illustrates four interconnects 9021′, 9022′, 9023′ and 9024′that are connected between circular MEMS mirror 9002 and four actuators9011, 9012, 9013 and 9014. The first and second segments of eachinterconnect are connected by joints. For example, interconnect 9021′includes a first segment 90212, a second segment 90211 and a joint 90213that is connected to the first and second segments and facilitatesrelative movement between the first and second interconnects. The jointmay be a ball joint or any other type of joint.

FIG. 59 illustrates ten non-limiting examples of interconnects.Interconnects 90215, 90216, 90217, 90218 and 90219 do not includejoints. Interconnects 90215′, 90216′, 90217′, 90218′ and 90219′ doinclude at least one joint. In addition, FIG. 59 illustratesinterconnects that include linear segments, nonlinear segments, onesegments, two segments and even nine segments. The interconnects mayinclude any number of segments, have segments of any shape, and mayinclude zero to multiple joints.

Response to Mechanical Vibrations

A scanning unit (e.g., scanning unit 104) may include the MEMS mirror,the actuators, the interconnector and other structural elements of theLIDAR system. Scanning unit 104 may be subjected to mechanicalvibrations that propagate along different directions. For example, aLIDAR system that is installed in a vehicle may be subjected todifferent vibrations (from different directions) when the vehicle movesfrom one point to another. If all actuators have the same structure anddimensions the response of the unit to some frequencies may be very high(high Q factor). By introducing a certain asymmetry between theactuators, scanning unit 104 may react to more frequencies, however, thereaction may be milder (low Q factor).

FIG. 60 illustrates a first pair of actuators 9011 and 9013 that areopposite to each other and are shorter (by DeltaL 9040) than actuatorsof a second pair of actuators 9012 and 9014. Actuators 9012 and 9014 areopposite to each other and are oriented to actuators 9011 and 9013. FIG.60 also illustrates L-shaped interconnects 9021, 9022, 9023 and 9024,and a circular MEMS mirror 9002. The resonance frequency of the unit maybe outside the frequency range of the mechanical vibrations. Theresonance frequency of the unit may exceed a maximal frequency of thecertain frequency range by a factor of at least two. The resonancefrequency of the unit is between four hundred hertz and one Kilohertz.

FIG. 61A illustrates a frame 9050 that surrounds the actuators 9011,9012, 9013 and 9014, the interconnects 9021, 9022, 9023 and 9024, andthe MEMS mirror 9002. Actuators 9011, 9012, 9013 and 9014 are connectedto the frame 9050 at their bases 9071, 9072, 9072 and 9074 respectively.In one embodiment, the width of the base may be any fraction (forexample below 50%) of the entire length of the actuator. In addition,the base may be positioned at any distance from point of connection ofthe actuator to the interconnect. For example, the base may bepositioned near an end of the actuators that is opposite to the end ofthe connector that is connected to the interconnect.

FIG. 61B illustrates a frame 9550 that surrounds the actuators 9511,9512, 9513 and 9514, connected via shaft 9590 to MEMS mirror 9002 thatis positioned on different plane than a plane of frame 9550, inaccordance with examples of the presently disclosed subject matter. Theinterconnects between actuators 9511, 9512, 9513 and 9514 and shaft 9590are not illustrated, for the sake of simplicity. Those interconnects mayhave similar shapes and characteristics to those discussed above withrespect to interconnects 9021, 9022, 9023 and 9024, but this is notnecessarily so. As exemplified in FIG. 61A, MEMS mirror 9002 may beactuated by actuators which are positioned in a different plane than theplane of MEMS mirror 9002. The movement of the actuators 9511, 9512,9513 and 9514 is transmitted to MEMS mirror 9002 by shaft 9590, which isconnected on its one end to the actuators, and on its other end to abase surface of MEMS mirror 9002. It is noted that shaft 9590 may bereplaced by any kind of rigid connector. Referring to the actuatorswhich move the shaft (which can of course be of any other number, andnot necessarily four as illustrated), it is noted that these actuatorsmay be actuated using any kind of actuation technique—e.g.,piezoelectric actuation, electrostatic actuation, electromagneticactuation, electromechanical actuation—including any actuation methoddiscussed in this disclosure. It is noted that MEMS mirrors mayimplemented actuation on a different plane for one-dimensional (1D)scanning or for two-dimensional (2D) scanning.

The disclosed position of the actuation assembly of MEMS mirror 9002 ina different plane behind the reflective surface plane allows to create areflector array (such as reflector array 312) which includes a pluralityof reflectors which are located in great proximity to one another. Thisincreases the usable portion of the surface of the reflectors array, andreduce the amount of undesired reflections (reflecting from parts of thereflector assembly which are not the mirrors surfaces). Also, locatingthe moving actuators behind MEMS mirror 9002 (and away from the opticaltransmission paths of light in the system) reduces the amount of photonswhich are reflected from the moving actuators in unintended direction,thus reducing the level of noise in the system. MEMS mirror 9002 andactuation surface (which includes the actuators and frame 9550) may bemanufactured on two different wafers, and connected to each other indifferent ways, such as those which are known in the art.

Monitoring the MEMS Mirror Using a Variable Capacitor

Consistent with the present disclosure, the orientation of the MEMSmirror may be estimated by monitoring the bending of the actuators thatare connected (via the interconnects) to the MEMS mirror. For example,LIDAR system 100 may include one or more variable capacitors. There maybe one variable capacitor per actuator, more than a single variablecapacitor per actuator, and/or less variable capacitors than actuators.For each variable capacitor, the capacitance of the variable capacitorrepresents a spatial relationship between the frame and an actuator. Thecapacitance of the variable capacitor may be a function of an overlaparea between one or more plates of the variable capacitor that areconnected to the frame and one or more other plates of the variablecapacitor that are connected to the actuator, especially to acircumference of the actuator that faces the frame.

FIG. 62 illustrates a frame 9050 that surrounds the actuators 9011,9012, 9013 and 9014, the interconnects 9021, 9022, 9023 and 9024, andthe MEMS mirror 9002. FIG. 62 also illustrates a variable capacitor 9061that is formed between the frame 9050 and actuator 9011. Variablecapacitor 9061 includes multiple plates first plates 90612 that areconnected to the actuator and multiple second plates 90611 that areconnected to the frame. It may be beneficial to have at least threevariable capacitors between at least three actuators and the frame. Forsimplicity of explanation only a single variable capacitor is shown. Thevariable capacitor may be located anywhere along the circumference ofthe actuator, and at any distance from the circumference of the actuatorthat is connected to the interconnect. In addition, the location of thevariable capacitor may be determined based on the shape and size of theplates of the variable capacitor, and the amount of bending that can beexperienced by different parts of the actuator. For example, positioningthe variable capacitor near the base will result in smaller changed inthe overlap area between the first and second plates, while positioningthe variable capacitor near the connection point to the interconnect mayresult in a lack of overlap between the first and second plates.

FIG. 62 also illustrates (from left to right) first and second plates(90611 and 90612) that fully overlap, then (as the actuator startsbending) mostly overlap (overlap area 9068), and then only slightlyoverlap (small overlap area 9068) when the actuator continues to bend.The first plates 90612 are coupled in parallel to each other. The secondplates 90611 are coupled in parallel to each other. The first and secondplates are coupled to a capacitance sensor 9065 that is configured tosense the capacitance of the variable capacitor. A controller of theLIDAR system may estimate the orientation of the MEMS mirror based onthe capacitance of one or variable capacitors.

FIG. 63 illustrates a frame 9050 that surrounds the actuators 9011,9012, 9013 and 9014, the interconnects 9021, 9022, 9023 and 9024, andthe MEMS mirror 9002. FIG. 63 also illustrates electrodes 9081, 9082,9083 and 9084 that are connected to actuators 9011, 9012, 9013 and 9014.The electrodes may be connected to any part of the actuators. Anactuator may be connected to multiple electrodes. The electrodes usuallyspread along significant regions of the actuator.

Monitoring the MEMS Mirror Using Dummy Piezoelectric Elements

Consistent with the present disclosure, the provided electrode mayconvey electrical signals for bending the actuator and/or for sensingthe bending of the actuator. The bending of the actuators may bemonitored by using actuators that include dummy elements. The dummyelements may be dummy electrodes and dummy piezoelectric elements. Adummy piezoelectric element is mechanically coupled to a piezoelectricelement that is subjected to a bending electrical field. Thepiezoelectric element is bended. This bending causes the dummypiezoelectric element to bend. The bending of the dummy piezoelectricelement can be measured by electrodes coupled to the dummy piezoelectricelement.

FIG. 64 illustrates frame 9050 that surrounds the actuators 9011, 9012,9013 and 9014, the interconnects 9021, 9022, 9023 and 9024, and the MEMSmirror 9002. FIG. 64 also illustrates electrodes 9081, 9082, 9083 and9084 that are connected to piezoelectric elements 9111, 9112, 9113 and9114 of actuators 9011, 9012, 9013 and 9014. Electrodes 9081, 9082, 9083and 9084 are used to convey bending control signals. FIG. 64 alsoillustrates electrodes 9091, 9092, 9093 and 9094 that are connected todummy piezoelectric elements 9011′, 9112′, 9113′ and 9114′ of actuators9011, 9012, 9013 and 9014. Electrodes 9091, 9092, 9093 and 9094 are usedto measure the state of dummy piezoelectric elements 9011′, 9112′, 9113′and 9114′. Electrodes 9081, 9082, 9083, 9084, 9091, 9092, 9093 and 9094usually cover a significant part of the piezoelectric elements. Itshould be noted that each piezoelectric element is positioned betweenpairs of electrodes, and that FIG. 64 illustrates only the externalelectrodes. Internal electrodes located between a substrate (or a body)of the actuator and the piezoelectric elements are not shown.

FIG. 65 is a cross sectional view of an actuator 9011, a feedback sensor9142 and a steering source signal 9140. The actuator 9011 may includesubstrate (or body) layer 9121, internal electrode 9081′, internal dummyelectrode 9091′, piezoelectric element 9111, dummy piezoelectric element9111′, external electrode 9081 and external dummy electrode 9091.Steering signal sensor 9140 sends steering signals SS1 9151 and SS2 9152to external electrode 9081 and internal electrode 9121 for bendingactuator 9011. Feedback sensor 9142 sensed the bending of the dullypiezoelectrical element 9111′ be measuring the electrical field betweeninternal dummy electrode 9091′ and external dummy electrode 9091. Itshould be noted that only one steering signal may be provided.

FIG. 66 illustrates that each actuator out of actuators 9011, 9012, 9013and 9014 can be formed from four major layers: external electrode layer(9124, 9134, 9144 and 9154), a piezoelectric layer (9123, 9133, 9143 and9153), internal electrode layer (9122, 9132, 9142 and 9152), and asubstrate (or body) layer (9121, 9131, 9141 and 9151).

Monitoring the MEMS Mirror by Measuring Dielectric Coefficient Changes

Consistent with the present disclosure, the bending of the actuator maychange the dielectric coefficient of the piezoelectric element.Accordingly, the actuator may be monitored by measuring changes in thedielectric coefficient of the piezoelectric element. The actuator may befed with electrical field induced by one or more control signals from acontrol signal source, the one or more control signals are fed to one ormore electrodes of LIDAR system 100, for example, a pair of electrodesthat are positioned on opposite sides of the piezoelectric element. Onecontrol signal, both control signals and/or a difference between thecontrol signals have an alternating bias component and a steeringcomponent. The bending of the body is responsive to the steeringcomponent. In some embodiments, the frequency of the alternating biascomponent may exceed a maximal frequency of the steering component (forexample, by a factor of at least ten); and the amplitude of thealternating bias component may be lower than an amplitude of thesteering component by any factor, for example, a factor that is notsmaller than one hundred. For example, the steering component may betens of volts while the alternating bias component may range betweentens to hundreds of millivolts. Therefore, a sensor of LIDAR system 100may be configured to sense dielectric coefficient changes of theactuator due to the bending of the actuator.

FIG. 67 illustrates an actuator that includes external electrode layer9124, piezoelectric layer 9123, internal electrode layer 9122 and asubstrate layer 9121. Steering signal source 9140 sends control signalSS1 9151 to external electrode layer 9124 and sends control signal SS29152 to internal electrode layer 9122. At least one of control signalsSS1 9151 and SS2 9152 or the difference between the control signalsincludes the alternating bias component and the steering component.Feedback sensor 9124 is coupled to external electrode layer 9124, and tointernal electrode layer 9122 and may sense (directly or indirectly)changes of the dielectric coefficients of piezoelectric layer 9123.Feedback sensor 9124 may be, for example, a current amplitude sensor ora combination of a current amplitude sensor and a phase shift sensor.The LIDAR sensor may include a controller that may be configured toreceive (from feedback sensor 9142) information about the dielectriccoefficient changes and to determine an orientation of the MEMS mirror.FIG. 67 also illustrates the steering signal source 9140 as including aninitial signals source 9141 that outputs the steering components (9161and 9164) of control signals SS1 9151 and SS2 9152. These steeringcomponents are mixed (by mixers 9163 and 9165) with the alternating biascomponents (generated by oscillators 9162 and 9165) to generate controlsignals SS1 9151 and SS2 9152. The actuator may be monitored by sensingthe resistance of the actuator.

FIG. 68 illustrates two electrodes 9211 and 9212 that are positioned attwo opposite ends of actuator 9011, and are used for measuring theresistance of the actuator. Electrode 9135 is used for bending theactuator. Electrodes 9211, 9212 and 9135 are electrically coupled tothree conductors 9201, 9202 and 9203.

FIG. 69 illustrates stress relief apertures 9220 that are formed inactuator 9011. The stress relief apertures of FIG. 69 are curved and aresubstantially parallel to each other. The number of the stress reliefapertures may differ from four, the slots may have any shape or size andmay differ from each other. In some of the previous figures thepiezoelectric element was positioned above the substrate. It should benoted that the piezoelectric element may be positioned below thesubstrate. Piezoelectric elements may be positioned below and above thesubstrate.

FIG. 70 illustrates actuator 9012 as including seven major layers:external electrode layer 9124, piezoelectric layer 9123, internalelectrode layer 9122, substrate (or body) layer 9121, additionalinternal electrode layer 9129, additional piezoelectric layer 9128, andadditional external electrode layer 9127. External electrode layer 9124,piezoelectric layer 9123 and internal electrode layer 9122 arepositioned above substrate layer 9121. Additional internal electrodelayer 9129, additional piezoelectric layer 9128, and additional externalelectrode layer 9127 are positioned below substrate layer 9121. Theadditional piezoelectric layer 9128 may equal the piezoelectric layer9123 or may differ from the piezoelectric layer 9123 by at least one outof size, shape and the like. Specifically, any of the electrode layersmay be the same or may differ from each other. Additional piezoelectriclayer 9128 and piezoelectric layer 9123 may be controlled independentlyfrom each other or in a dependent manner. Additional piezoelectric layer9128 may also be used for bending the actuator downwards whilepiezoelectric layer 9123 may be used for bending the actuator upwards.The additional piezoelectric layer 9128 may be used as a dummypiezoelectrical sensor (for monitoring the actuator) when thepiezoelectric layer 9123 is activated for bending the actuator. In oneexample, the piezoelectric layer 9122 may be used as a dummypiezoelectrical sensor (for monitoring the actuator) when thepiezoelectric layer 9128 is activated for bending the actuator.

FIG. 71 illustrates, from top to bottom, (i) an idle state of mirror9002, (ii) a downward bent actuator that lowers the circumference ofMEMS mirror 9002, and (iii) an upward bent actuator that elevates thecircumference of MEMS mirror 9002. MEMS mirror 9002 is coupled to theactuator via interconnect 9300. The MEMS mirror 9002 may include a thinreflecting surface that is reinforced by reinforcing elements.

FIGS. 72 and 73 illustrate frame 9050 and a backside of MEMS mirror9002. For simplicity of explanation the actuators are not shown. Thereinforcing elements 9003 include concentric rings and radial segment.Any arrangement and shapes of reinforcing elements may be provided.

The orientation of the MEMS mirror may be monitored by illuminating thebackside of the MEMS mirror 9002. It may be beneficial to illuminate atleast one area of the MEMS mirror and to sense reflected light in atleast three locations. The orientation of the MEMS mirror may bemonitored by illuminating the backside of the MEMS mirror 9002. It maybe beneficial to illuminate at least one area of the back side of theMEMS mirror and to sense reflected light in at least three locations. Itis noted that LIDAR system 100 may include a dedicated light source forilluminating the back side of the MEMS mirror. The dedicated lightsource (e.g., LED) may be located behind the mirror (i.e., away from itsmain reflective sensor used for the deflection of light from the atleast one light source 112). Alternatively, LIDAR system 100 may includeoptics to direct light onto the back side of the mirror. In someexamples, light directed at the back side of the MEMS mirror (e.g. lightof the dedicated light source) is confined to a backside area of themirror, and prevented from reaching the main reflective side of the MEMSmirror. The processing of the signals of the back side sensors may beexecuted by processor 118, but may also be processed by a dedicatedcircuitry integrated into a chip positioned within a casing of themirror. The processing may include comparing the reflected signals todifferent back side sensors (e.g. 9231, 9232, 9233), subtracting suchsignals, normalizing such signals, etc. The processing of such signalsmay be based on information collected during a calibration phase.

FIG. 74 illustrates an illuminated region 9030 and three sensors 9231,9232 and 9233 that are positioned below the MEMS mirror and are arrangedto sense light that is reflected (dashed lines) at three differentdirections thereby allowing to sense the orientation of the MEMS mirror.The illuminated region may be located anywhere at the backside of theMEMS mirror, and may have any shape and size. In embodiment, the MEMSmirror may not be parallel to a window of the Lidar system. The MEMSmirror may receive a light that passes through a window of the Lidarsystem and deflects the reflected mirror to provide deflected light thatmay pass through the window and reach other components (such as lightsensors) of the Lidar system. A part of the deflected light may bereflected (by the window) backwards—toward the MEMS mirror, the frame orthe actuators. However, when the MEMS mirror and the window are parallelto each other the light may be repetitively reflected by the MEMS mirrorand the window thereby generating unwanted light artifacts. These lightartifacts may be attenuated and even prevented by providing a windowthat is not parallel to the MEMS mirror or when the optical axis of theMEMS mirror and the optical axis of the window are not parallel to eachother. When either one of the MEMS mirror and the window are curved orhave multiple sections that are oriented to each other—then it may bebeneficial that no part of the MEMS mirror should be parallel to anypart of the window. The angle between the window and the MEMS mirror maybe set so that the window does not reflect light towards the MEMSmirror, when the MEMS mirror is at an idle position or even when theMEMS mirror is moved by any of the actuators.

It is noted that illuminating a backside of the MEMS mirror may beimplemented when the back of the mirror is substantially uniformlyreflective (e.g. a flat back, without reinforcement ribs). However, thisis not necessarily the case, and the back of the mirror may be design toreflect light in a patterned non-uniform way. The patterned reflectionbehavior of the back side of the mirror may be achieved in various way,such as surface geometry (e.g. protrusions, intrusions), surfacetextures, differing materials (e.g., Silicon, Silicon Oxide, metal), andso on. Optionally, the MEMS mirror may include a patterned back side,having a reflectivity pattern on at least a part of the back surface ofthe mirror, which cast a patterned reflection of the back sideillumination (e.g. from the aforementioned back side dedicated lightsource) onto the back side sensors (e.g. 9231, 9232, 9233). Thepatterned back side may optionally include parts of the optionalreinforcing elements 9003 located at the back of the MEMS mirror, butthis is not necessarily so. For example, the reinforcing elements 9003may be used to create shadows onto the sensors 9231 etc. at some angles(or to deflect the light to a different angle), which means thatmovement of the mirror would change the reflection on the sensor fromshadowed to bright.

Optionally, the processing of the outputs of the backside sensors (9231,9232, 9233 etc.) may take into account a reflectivity pattern of thebackside (e.g. resulting from the pattern of the reinforcement ribs).Thus, the processing may use the patterning resulting from the backsidesurface pattern as part of the feedback being processed. Optionally, thebackside mirror feedback option discussed herein may utilize a backsidereflectivity pattern which can be processed by data from backsidesensors which are located in greater proximity to the mirror (comparingto the uniform reflectivity implementation), which reduce the size ofthe MEMS assembly and improves its packaging. For example, the back sidepattern may de designed so that the reflection pattern includes sharptransitions between dark and bright reflections. Those sharp transitionsmean that even small changes in the angle/position of the MEMS mirrorwould cause significant changes in the light reflected to detectorswhich are positioned in even close distance. In addition, thereflectivity pattern may be associated with a reflectivity gradient, notsharp edges (i.e.—light or shadow). This embodiment, may have linearityfrom the first option of sharp edges, thus it may ease thepost-processing process, and also support a larger angles range and willprobably be less sensitive to assembly tolerances.

MEMS Mirror that is not Parallel to a Window of the LIDAR System

Consistent with the present disclosure, the MEMS mirror may receive alight that passes through a window of the LIDAR system and deflects thereflected mirror to provide deflected light that may pass through thewindow and reach other components (such as light sensors) of LIDARsystem 100. A part of the deflected light may be reflected (by thewindow) backwards, toward the MEMS mirror, the frame or the actuators.When the MEMS mirror and the window are parallel to each other, thelight may be repetitively reflected by the MEMS mirror and the windowthereby generating unwanted light artifacts. These light artifacts maybe attenuated and even prevented by providing a window that is notparallel to the MEMS mirror or when the optical axis of the MEMS mirrorand the optical axis of the window are not parallel to each other. Wheneither one of the MEMS mirror and the window are curved or have multiplesections that are oriented to each other, then it may be beneficial thatno part of the MEMS mirror should be parallel to any part of the window.The angle between the window and the MEMS mirror may be set so that thewindow does not reflect light towards the MEMS mirror, when the MEMSmirror is at an idle position or even when the MEMS mirror is moved byany of the actuators.

FIG. 75 illustrates a housing 9320 that includes window 9322. Thehousing encloses the MEMS mirror 9002. Housing 9320 may be a sealedhousing that may be manufactured using wafer level packaging or anyother technology. Housing 9320 includes a base 9310. Base 9310 may betransparent or not transparent. A transparent base may be useful whenthe backside of MEMS mirror 9002 is monitored by illumination. Light9601 passes through window 9322 and impinges on MEMS mirror 9002. MEMSmirror 9002 deflects the light to provide a deflected light 9602. A partof the deflected light may pass through window 9322, but another part9603 is reflected by mirror 9322 towards housing 9320. Accordingly, part9603 may not reflected towards MEMS mirror 9002.

FIG. 76 illustrates the housing 9320 as including an upper part. Theupper part includes mirror 9320 and two sidewalls 9321 and 9323. Anintermediate part of the housing may be formed from the exterior part(such as but not limited to frame 9050) of an integrated circuit thatincludes various layers (such as 9121 and 9122). The integrated circuitmay include MEMS mirror 9002 (having an upper reflecting surface 9004,various intermediate elements of layers 9121 and 9122, and reinforcingelements 9003), interconnects 9022 and 9021, actuators 9012 and 9014. Abonding layer 9301 may be positioned between the integrated circuit andbase 9310.

FIG. 77 illustrates the housing 9320 that includes a transparent base.For simplicity of explanation this figure illustrates illumination unit9243, beam splitter 9263 and a sensor 9253. Illumination unit 9243 andthe light sensor 9253 are positioned outside the housing.

FIG. 78 illustrates an anti-reflective layer 9380 that is positioned ontop of the actuators, and the interconnects. FIG. 79 illustratesanti-reflective layer 9380 that is positioned on top of the actuators,frame and the interconnects. FIG. 80 illustrates anti-reflective layer9380 that is positioned on top of the frame. Any of the mentioned aboveanti-reflective layers may be replaced by one or more anti-reflectiveelements that may differ from a layer. The anti-reflective element maybe parallel to the window, oriented in relation to the window, and thelike.

FIG. 81 illustrates a housing that has a window that is parallel to theMEMS window. The housing includes a transparent base. For simplicity ofexplanation this figure illustrates illumination unit 9243, beamsplitter 9263 and a sensor 9253. Illumination unit 9243 and the lightsensor 9253 are positioned outside the housing. The MEMS mirror may beof any shape or size. For example, the MEMS mirror may be rectangular.

FIGS. 82 and 83 illustrate a rectangular MEMS mirror 9402, two actuators9404 and 9407, two interconnects 9403 and 9406, electrodes 9410 and9413, and a rectangular frame that includes an upper part 9504, a lowerpart 9408 and two insulating parts 9411 and 9422 that are connectedbetween the upper and lower parts of the frame. In FIG. 82, actuators9404 and 9407 are parallel to each other opposite, face opposite sidesof the MEMS mirror and are connected to opposite parts of the frame. InFIG. 83, actuators 9404 and 9407 are parallel to each other opposite,face opposite sides of the MEMS mirror and are connected to the sameside of the frame.

FIG. 84 illustrates a rectangular MEMS mirror 9402, four actuators 9404,9407, 9424, 9427, four interconnects 9403, 9406, 9423 and 9436, fourelectrodes 9410, 9413, 9440 and 9443, and a rectangular frame thatincludes an upper part 9504, a lower part 9408 and two insulating parts9411 and 9422 that are connected between the upper and lower parts ofthe frame. The four actuators face four facets of MEMS mirrors 9402 andeach is connected to a different facet of the frame. Although FIGS.56-84 illustrate a single MEMS mirror. LIDAR system 100 may include anarray of multiple MEMS mirrors. Any number of MEMS mirrors may bemonitored in order to provide feedback that is used to control any ofthe multiple MEMS mirrors. For example, if there are more N MEMS mirrorsthan any number between 1 and N, MEMS mirrors may be monitored toprovide feedback that may be used for monitoring any number of MEMSmirrors of the N MEMS mirrors.

In one embodiment, LIDAR system 100 may include a window for receivinglight; a microelectromechanical (MEMS) mirror for deflecting the lightto provide a deflected light; a frame; actuators; interconnect elementsthat may be mechanically connected between the actuators and the MEMSmirror. Each actuator may include a body and a piezoelectric element.The piezoelectric element may be configured to bend the body and movethe MEMS mirror when subjected to an electrical field. When the MEMSmirror is positioned at an idle positioned it may be oriented inrelation to the window. The light may be reflected light that may bewithin at least a segment of a field of view of the LIDAR system. Thelight may be transmitted light from a light source of the LIDAR system.During a first period the light is a transmitted light from a lightsource of the LIDAR system and during a second period the light isreflected light that is within at least a segment of a field of view ofthe LIDAR system.

In another embodiment, LIDAR system 100 may include at least oneanti-reflective element that may be positioned between the window andthe frame The anti-reflective element may be oriented in relation to thewindow. The angle of orientation between the MEMS mirror and the windowmay range between 20 and 70 degrees. The window may be shaped andpositioned to prevent a reflection of any part of the deflected lighttowards the MEMS mirror. The MEMS mirror may be oriented to the windoweven when moved by at least one of the actuators. An interconnectelement of the interconnect elements may include a first segment thatmay be connected to the MEMS mirror and a second segment that may beconnected to the actuator, wherein the first segment and the secondsegments may be mechanically coupled to each other.

In related embodiments: the first segment may be oriented bysubstantially ninety degrees to the second segment; the first segmentmay be connected to a circumference of the MEMS mirror and may beoriented by substantially ninety degrees to circumference of the MEMSmirror; the first segment may be directed towards a center of the MEMSmirror when the MEMS mirror is positioned at an idle position; thesecond segment connected to a circumference of the actuator and may beoriented by substantially ninety degrees to the circumference of theactuator; a longitudinal axis of the second segment may be substantiallyparallel to a longitudinal axis of the actuator; the first segment andthe second segment may be arranged in an L-shape when the MEMS mirror ispositioned at an idle position; the interconnect element may include atleast one additional segment that may be mechanically coupled betweenthe first and second segments, the first segment and the second segmentmay differ from each other by length; the first segment and the secondsegment may differ from each other by width; the first segment and thesecond segment may differ from each other by a shape of a cross section;the first segment and the second segment may be positioned at a sameplane as the MEMS mirror when the MEMS mirror is positioned at an idleposition. The first segment and the second segment may be positioned ata same plane as the actuators.

In another embodiment, LIDAR system 100 may include a MEMS mirror thatmay have an elliptical shape (e.g., the MEMS mirror may be circular),and wherein the actuators may include at least three independentlycontrolled actuators. Each pair of actuator and interconnect elementsmay be directly connected between the frame and the MEMS mirror. TheMEMS mirror may be operable to pivot about two axes of rotation.

In related embodiments, the actuators may include at least fourindependently controlled actuators; a longitudinal axis of the MEMSmirror corresponds to a longitudinal axis of the light beam; alongitudinal axis of MEMS mirror corresponds to a longitudinal axis of adetector array of the LIDAR system; the actuators may include a firstpair of actuators that may be opposite to each other along a firstdirection and a second pair of actuators that may be opposite to eachother along a second direction; the first pair of actuators may differfrom the second pair of actuators; the window, the MEMS mirror, theframe and the actuators may form a unit; the unit may responddifferently to mechanical vibration that propagate along the firstdirection and to mechanical vibrations that propagate along the seconddirection; the actuators of the first pair, when idle, may have a lengththat substantially differs from a length of the actuators of the secondpair, when idle; the actuators of the first pair, when idle, may have ashape that substantially differs from a shape of the actuators of thesecond pair, when idle; during operation, the LIDAR system may besubjected to mechanical vibrations having a certain frequency range; theresonance frequency of a unit may be outside the certain frequencyrange; the resonance frequency of the unit may exceed a maximalfrequency of the certain frequency range by a factor of at least two;the resonance frequency of the unit may be between four hundred hertzand one Kilohertz; an actuator may include a piezoelectric element thatmay be positioned below the body of the actuator and another actuatormay include a piezoelectric element that may be positioned above thebody of the other piezoelectric element; the actuator may include apiezoelectric element that may be positioned above the body of thepiezoelectric element; the LIDAR system may further include a controllerwhich may be configured to receive from the sensor an indication of thestate of the additional piezoelectric element; the controller may beconfigured to control the actuator based on the indication of the stateof the additional piezoelectric element; and the controller may beconfigured to determine an orientation of the MEMS mirror based on theindication of the state of the additional piezoelectric element.

In another embodiment, LIDAR system 100 may include a variable capacitorand a sensor. The capacitance of the variable capacitor represents aspatial relationship between the frame and an actuator of the actuators,the sensor may be configured to sense the capacitance of the variablecapacitor.

In related embodiments, the variable capacitor may include a first platethat may be connected to the actuator and a second plate that may beconnected to the frame, the spatial relationship between the frame andthe actuator determines an overlap between the first plate and thesecond plate; the variable capacitor may include multiple first platesthat may be connected to the actuator and multiple second plates thatmay be connected to the frame; the actuator has a first end that may bemechanically connected to the frame and a second end that may beopposite to the first end and may be mechanically connected to theinterconnect element; a distance between the variable capacitor and thefirst end exceeds a distance between the variable capacitor and thesecond end; the actuator has a first end that may be mechanicallyconnected to the frame and a second end that may be opposite to thefirst end and may be mechanically connected to the interconnect element;and a distance between the variable capacitor and the first end may besmaller than a distance between the variable capacitor and the secondend.

In another embodiment, LIDAR system 100 may include a controller whichmay be configured to receive an indication of a capacitance of thevariable capacitor and to determine an orientation of the MEMS mirrorbased on the capacitance of the variable capacitor. A piezoelectricelement may be configured to bend the body and move the MEMS mirror whensubjected to an electrical field induced by a control signal from acontrol signal source, the control signal may be fed to an electrode ofthe LIDAR system.

The control signal has an alternating bias component and a steeringcomponent. A bending of the body may be responsive to the steeringcomponents, wherein a frequency of the alternating bias componentexceeds a maximal frequency of the steering component. The sensor may beconfigured to sense dielectric coefficient changes of the actuator dueto the bending of the actuator.

In related embodiments, the sensor may be a current amplitude sensor;the sensor may also be a current amplitude sensor and a phase shiftsensor; an amplitude of the alternating bias component may be lower thanan amplitude of the steering component by a factor of at least onehundred; the LIDAR system may further include a controller which may beconfigured to receive information about the dielectric coefficientchanges and to determine an orientation of the MEMS mirror; the windowmay belong to a housing. The housing may be a sealed housing thatencloses the MEMS mirror, the frame, and the actuators; the housing mayinclude a transparent region that may be positioned below the MEMSmirror; the LIDAR system may further include at least one optical sensorand at least one light source, the at least one light source may beconfigured to transmit at least one light beam through the transparentregion and towards a backside of the MEMS mirror; the at least oneoptical sensor may be configured to receive light from the backside ofthe MEMS mirror; the LIDAR system may include a controller which may beconfigured to determine an orientation of the MEMS mirror based oninformation from the at least one optical sensor, different parts of thehousing may be formed by wafer level packaging; the frame may belong toan integrated circuit that forms a bottom region of the housing; aninterconnect element of the interconnect elements may include multiplesegments that may be mechanically coupled to each other by at least onejoint; the joint may be a ball joint; and the joint may also be a MEMSjoint.

The foregoing description has been presented for purposes ofillustration. It is not exhaustive and is not limited to the preciseforms or embodiments disclosed. Modifications and adaptations will beapparent to those skilled in the art from consideration of thespecification and practice of the disclosed embodiments. Additionally,although aspects of the disclosed embodiments are described as beingstored in memory, one skilled in the art will appreciate that theseaspects can also be stored on other types of computer readable media,such as secondary storage devices, for example, hard disks or CD ROM, orother forms of RAM or ROM, USB media, DVD, Blu-ray, or other opticaldrive media.

Computer programs based on the written description and disclosed methodsare within the skill of an experienced developer. The various programsor program modules can be created using any of the techniques known toone skilled in the art or can be designed in connection with existingsoftware. For example, program sections or program modules can bedesigned in or by means of .Net Framework, .Net Compact Framework (andrelated languages, such as Visual Basic, C, etc.). Java, C++,Objective-C, HTML, HTML/AJAX combinations, XML, or HTML with includedJava applets.

Moreover, while illustrative embodiments have been described herein, thescope of any and all embodiments having equivalent elements,modifications, omissions, combinations (e.g., of aspects across variousembodiments), adaptations and/or alterations as would be appreciated bythose skilled in the art based on the present disclosure. Thelimitations in the claims are to be interpreted broadly based on thelanguage employed in the claims and not limited to examples described inthe present specification or during the prosecution of the application.The examples are to be construed as non-exclusive. Furthermore, thesteps of the disclosed methods may be modified in any manner, includingby reordering steps and/or inserting or deleting steps. It is intended,therefore, that the specification and examples be considered asillustrative only, with a true scope and spirit being indicated by thefollowing claims and their full scope of equivalents.

What is claimed is:
 1. A LIDAR system, comprising: at least oneprocessor configured to: control at least one light source in a mannerenabling light flux to vary over a scan of a field of view using lightfrom the at least one light source; control projection of at least afirst light emission directed toward a first portion of the field ofview to determine an absence of objects in the first portion of thefield of view at a first distance; when an absence of objects isdetermined in the first portion of the field of view based on the atleast a first light emission, control projection of at least a secondlight emission directed toward the first portion of the field of view toenable detection of an object in the first portion of the field of viewat a second distance, greater than the first distance; and controlprojection of at least a third light emission directed toward the firstportion of the field of view to determine an existence of an object inthe first portion of the field of view at a third distance, greater thanthe second distance.
 2. The LIDAR system of claim 1, wherein the atleast one processor is further configured to control at least one lightdeflector in order to scan the field of view, such that during ascanning cycle, the at least one light deflector is located in aplurality of different instantaneous positions.
 3. The LIDAR system ofclaim 2, wherein the at least one processor is configured to coordinatethe at least one light deflector and the at least one light source suchthat when the at least one light deflector is located at a particularinstantaneous position, a light beam is deflected by the at least onelight deflector from the at least one light source towards the field ofview and reflections from an object in the field of view are deflectedby the at least one light deflector toward at least one sensor.
 4. TheLIDAR system of claim 2, wherein the at least one processor is furtherconfigured to control the at least one light deflector such that the atleast a first light emission, the at least a second light emission, andthe at least a third light emission are projected toward the firstportion of the field of view corresponding to a single instantaneousposition of the at least one light deflector.
 5. The LIDAR system ofclaim 2, wherein the at least one processor is configured to use the atleast a third light emission and at least one of: the at least a firstlight emission and the at least a second light emission, to determinethe existence of the object in the first portion of the field of view atthe third distance.
 6. The LIDAR system of claim 2, wherein the at leastone processor is further configured to control the at least one lightdeflector such that the at least a first light emission, the at least asecond light emission, and the at least a third light emission areprojected toward the first portion of the field of view from differentinstantaneous positions of the at least one light deflector.
 7. TheLIDAR system of claim 2, wherein the at least one processor is furtherconfigured to control the at least one light deflector such that the atleast a first light emission, the at least a second light emission, andthe at least a third light emission are projected toward the firstportion of the field of view in a single scanning cycle.
 8. The LIDARsystem of claim 2, wherein the at least one processor is furtherconfigured to control the at least one light deflector such that the atleast a first light emission, the at least a second light emission, andthe at least a third light emission are each projected toward the firstportion of the field of view in different scanning cycles.
 9. The LIDARsystem of claim 8, wherein the at least one processor is furtherconfigured to control the at least one light source such that the atleast a second light emission has a light intensity greater than lightintensity of the at least a first light emission, and the at least athird light emission has a light intensity greater than a lightintensity of the at least a second light emission.
 10. The LIDAR systemof claim 1, wherein the at least one processor is further configured tocontrol the at least one light source such that the at least a firstlight emission, the at least a second light emission, and the at least athird light emission are associated with substantially a same lightintensity.
 11. The LIDAR system of claim 1, wherein the at least oneprocessor is further configured to control projection of the at least athird light emission directed toward the first portion when, based ondetection of at least one of the at least a first light emission and theat least a second light emission, the absence of objects is determinedin the first portion at the first distance.
 12. The LIDAR system ofclaim 1, wherein the at least one processor is further configured tocontrol projection of the at least a third light emission directedtowards the first portion when, based on detection of the at least asecond light emission, the absence of objects is determined in the firstportion at the second distance.
 13. The LIDAR system of claim 1, whereinthe at least one processor is further configured to alter a light sourceparameter associated with the first portion such that during a samescanning cycle light flux of light directed to the first portion isgreater than light flux of light directed to at least one other portionof the field of view.
 14. The LIDAR system of claim 1, wherein the atleast one processor is further configured to control the at least onelight source such that the at least a first light emission and the atleast a third light emission are each associated with a differingwavelength.
 15. The LIDAR system of claim 1, wherein the at least oneprocessor is further configured to control the at least one light sourcesuch that an accumulated energy density of the light in the firstportion of the field of view does not exceed a maximum permissibleexposure.
 16. A method for detecting objects using a LIDAR system, themethod comprising: controlling at least one light source in a mannerenabling light flux to vary over a scan of a field of view using lightfrom the at least one light source; controlling projection of at least afirst light emission directed toward a first portion of the field ofview to determine an absence of objects in the first portion of thefield of view at a first distance; when an absence of objects isdetermined in the first portion of the field of view based on the atleast a first light emission, controlling projection of at least asecond light emission directed toward the first portion of the field ofview to enable detection of an object in the first portion of the fieldof view at a second distance, greater than the first distance; andcontrolling projection of at least a third light emission directedtoward the first portion of the field of view to determine an existenceof an object in the first portion of the field of view at a thirddistance, greater than the second distance.
 17. The method of claim 16,further comprising: controlling projection of the at least a third lightemission directed towards the first portion when, based on detection ofat least one of the at least a first light emission and the at least asecond light emission, the absence of objects is determined in the firstportion at the first distance.
 18. The method of claim 16, furthercomprising: controlling projection of the at least a third lightemission directed towards the first portion when, based on detection ofthe at least a second light emission, the absence of objects isdetermined in the first portion at the second distance.
 19. The methodof claim 16, further comprising: altering a light source parameterassociated with the first portion such that light flux of light directedto the first portion is greater than light flux of light directed to atleast one other portion of the field of view.
 20. The method of claim16, further comprising: controlling the at least one light source suchthat the at least a first light emission, the at least a second lightemission, and the at least a third light emission are associated withsubstantially a same light intensity.
 21. The method of claim 16,further comprising: using the at least a third light emission and atleast one of: the at least a first light emission and the at least asecond light emission, to determine the existence of the object in thefirst portion of the field of view at the third distance.
 22. Anon-transitory computer-readable storage medium storing instructionsthat, when executed by at least one processor, cause the at least oneprocessor to perform a method for detecting objects using a LIDARsystem, the method comprising: controlling at least one light source ina manner enabling light flux to vary over a scan of a field of viewusing light from the at least one light source; controlling projectionof at least a first light emission directed toward a first portion ofthe field of view to determine an absence of objects in the firstportion of the field of view at a first distance; when an absence ofobjects is determined in the first portion of the field of view based onthe at least a first light emission, controlling projection of at leasta second light emission directed toward the first portion of the fieldof view to enable detection of an object in the first portion of thefield of view at a second distance, greater than the first distance; andcontrolling projection of at least a third light emission directedtoward the first portion of the field of view to determine an existenceof an object in the first portion of the field of view at a thirddistance, greater than the second distance.